[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-microsoft-context-intelligence-session-navigation":3,"mdc-y90obp-key":31,"related-repo-microsoft-context-intelligence-session-navigation":4450,"related-org-microsoft-context-intelligence-session-navigation":4531},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":20,"repoUrl":21,"updatedAt":22,"license":23,"forks":24,"topics":25,"repo":26,"sourceUrl":29,"mdContent":30},"context-intelligence-session-navigation","navigate and extract session data","Use when extracting session data directly from JSONL files — the baseline path when the graph server is unavailable or when operating outside graph-analyst",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"microsoft","Microsoft","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fmicrosoft.png",[12,16,17],{"name":13,"slug":14,"type":15},"Data Analysis","data-analysis","tag",{"name":9,"slug":8,"type":15},{"name":18,"slug":19,"type":15},"Agents","agents",3,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Famplifier-bundle-context-intelligence","2026-07-07T06:52:40.507052","MIT",4,[],{"repoUrl":21,"stars":20,"forks":24,"topics":27,"description":28},[],"Context Intelligence bundle for the Amplifier project","https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Famplifier-bundle-context-intelligence\u002Ftree\u002FHEAD\u002Fskills\u002Fcontext-intelligence-session-navigation","---\nname: context-intelligence-session-navigation\ndescription: 'Use when extracting session data directly from JSONL files — the baseline path when the graph server is unavailable or when operating outside graph-analyst'\nversion: 0.2.0\nlicense: MIT\n---\n\n# Context Intelligence Session Navigation\n\nThis skill covers navigation of flat JSONL session files written by the `LoggingHandler`. These files are the universal baseline — always present regardless of whether graph stores are configured. Use shell tools (`jq`, `grep`, `wc`, `head`) to extract data safely.\n\nFor the complete event-by-event field reference, see `context\u002Fevent-schema.md`.\nFor ready-to-use jq\u002Fgrep recipes, see `context\u002Fsafe-extraction-patterns.md`.\n\n---\n\n## Disk Layout\n\nResolve the root once before any discovery:\n\n```bash\nCONTEXT_INTELLIGENCE_ROOT=\"${AMPLIFIER_CONTEXT_INTELLIGENCE_BASE_PATH:-$HOME\u002F.amplifier\u002Fprojects}\"\n```\n\n```\n$CONTEXT_INTELLIGENCE_ROOT\u002F{project-slug}\u002Fsessions\u002F{session_id}\u002Fcontext-intelligence\u002F\n├── events.jsonl      # one JSON object per line, append-only\n└── metadata.json     # session metadata, written on start, updated on end\n```\n\n- `$CONTEXT_INTELLIGENCE_ROOT` — resolved from the idiom `\"${AMPLIFIER_CONTEXT_INTELLIGENCE_BASE_PATH:-$HOME\u002F.amplifier\u002Fprojects}\"` (unset → legacy default). **Relocation is reader-visible ONLY via this env var.** The hook's `config.base_path` moves where the *writer* stores captures, but readers (this skill, `discover.py`, the recipe) resolve the root solely from the env var — so always relocate via `AMPLIFIER_CONTEXT_INTELLIGENCE_BASE_PATH`, not `config.base_path` alone, or readers will look in the wrong place.\n- `{project-slug}` — derived from the full working directory path (see Project Slug Algorithm below)\n- `{session_id}` — unique session identifier (UUID or UUID with agent suffix for child sessions)\n- `context-intelligence\u002F` — subdirectory containing the session data files\n- `events.jsonl` — append-only log of every event the kernel emits during the session\n- `metadata.json` — compact session metadata for quick lookup without parsing the full event log\n\nExample paths (with root resolved):\n\n```\n$CONTEXT_INTELLIGENCE_ROOT\u002F-home-user-myapp\u002Fsessions\u002F55c8841a-1234-5678-9abc-def012345678\u002Fcontext-intelligence\u002Fevents.jsonl\n$CONTEXT_INTELLIGENCE_ROOT\u002F-home-user-myapp\u002Fsessions\u002F55c8841a-1234-5678-9abc-def012345678\u002Fcontext-intelligence\u002Fmetadata.json\n```\n\n> **⚠ MARKER RULE — the defect this prevents:** Every discovery glob MUST include the\n> `context-intelligence\u002F` path segment and MUST NOT stop at `sessions\u002F\u003Cid>\u002F`:\n>\n> ```\n> CORRECT:  \"$CONTEXT_INTELLIGENCE_ROOT\"\u002F*\u002Fsessions\u002F*\u002Fcontext-intelligence\u002Fevents.jsonl\n> WRONG:    \"$CONTEXT_INTELLIGENCE_ROOT\"\u002F*\u002Fsessions\u002F*\u002Fmetadata.json   # catches Amplifier core's files\n> ```\n>\n> **Why:** Amplifier core writes `sessions\u002F\u003Cid>\u002Fmetadata.json` with NO `context-intelligence\u002F`\n> segment. Globbing one level too shallow latches onto core's files and produces a confident\n> wrong count.\n>\n> **Canonical marker = `events.jsonl`.** The Python readers (`discover.py`, the workflow\n> recipe) treat `context-intelligence\u002Fevents.jsonl` as the single discriminator of a real\n> capture. `metadata.json` is used here only to read fields (`workspace`, `status`, …); both\n> files are written together, so either glob includes the `context-intelligence\u002F` segment and\n> avoids the false-positive. When you need a strict capture count that matches the code,\n> glob `events.jsonl`, not `metadata.json`.\n\n> **⚠ FAIL-LOUD RULE:** When zero captures are found, say exactly `\"looked in \u003Croot>, found 0\"` —\n> never report a confident count from a shallower glob, never silently fall back to a different path.\n\n---\n\n## Record Format\n\nEach line in `events.jsonl` is a single JSON object with exactly **four** fields, always in this order:\n\n```json\n{\"event\":\"tool:pre\",\"workspace\":\"my-project\",\"timestamp\":\"2026-03-10T11:13:09.792+00:00\",\"data\":{...}}\n```\n\n| Field | Type | Description |\n|-------|------|-------------|\n| `event` | string | Event name in `{namespace}:{action}` format |\n| `workspace` | string | Workspace scope — always present, empty string `\"\"` when not configured |\n| `timestamp` | string | ISO 8601 timestamp of when the event was recorded |\n| `data` | object | Raw event payload, exactly as the kernel emitted it |\n\n**Key principle:** No field promotion, no level classification, no payload mutation. What the kernel emits is exactly what gets stored in `data`. The `workspace` field is the only addition the hook makes — it is injected at write time from `ConfigResolver.workspace`.\n\n---\n\n## metadata.json\n\nWritten on `session:start` or `session:fork`, updated on `session:end`.\n\n### Required Fields (always present)\n\n| Field | Type | Description |\n|-------|------|-------------|\n| `format` | string | Schema family identifier, always `\"context-intelligence\"` |\n| `version` | string | Schema version, always `\"1.0.0\"` |\n| `session_id` | string | Unique session identifier |\n| `workspace` | string | Workspace scope — same value as in `events.jsonl`, empty string if not configured |\n| `parent_id` | string | Parent session identifier (empty string for root sessions) |\n| `started_at` | string | ISO 8601 timestamp |\n| `status` | string | `\"running\"` \u002F `\"completed\"` \u002F `\"failed\"` \u002F `\"cancelled\"` |\n| `working_dir` | string | Working directory path |\n\n### Optional Fields (omitted when absent — no nulls)\n\n| Field | Type | Description |\n|-------|------|-------------|\n| `agent_name` | string | Agent name (e.g., `\"foundation:explorer\"`) |\n| `parallel_group_id` | string | Parallel execution group identifier |\n| `recipe_name` | string | Recipe name if in recipe context |\n| `recipe_step` | string | Recipe step if in recipe context |\n| `ended_at` | string | ISO 8601 timestamp (added on `session:end`) |\n\nOptional fields are omitted entirely when absent — no null values, compact JSON.\n\nExample (minimal root session):\n\n```json\n{\"format\":\"context-intelligence\",\"version\":\"1.0.0\",\"session_id\":\"55c8841a-...\",\"workspace\":\"my-project\",\"parent_id\":\"\",\"started_at\":\"2026-03-10T11:13:09.000+00:00\",\"status\":\"running\",\"working_dir\":\"\u002Fhome\u002Fuser\u002Fmyapp\"}\n```\n\nExample (child session with optional fields):\n\n```json\n{\"format\":\"context-intelligence\",\"version\":\"1.0.0\",\"session_id\":\"55c8841a-...-foundation:explorer\",\"workspace\":\"my-project\",\"parent_id\":\"1cb9e5f5-...\",\"started_at\":\"2026-03-10T11:13:09.000+00:00\",\"status\":\"completed\",\"ended_at\":\"2026-03-10T11:15:42.000+00:00\",\"working_dir\":\"\u002Fhome\u002Fuser\u002Fmyapp\",\"agent_name\":\"foundation:explorer\",\"recipe_name\":\"code-review\",\"recipe_step\":\"analyze\"}\n```\n\n---\n\n## Workspace and Project Slug\n\n**Workspace** scopes all event data. It is written into every `events.jsonl` line and `metadata.json`. Two concepts work together:\n\n| Concept | Purpose | Where used |\n|---------|---------|------------|\n| `project_slug` | Directory name under `$CONTEXT_INTELLIGENCE_ROOT\u002F` | On-disk path |\n| `workspace` | Field in every record | Querying and filtering |\n\nBy **default** workspace equals `project_slug` (both derived from the working directory). They can differ when workspace is set explicitly via `settings.yaml` or env var — for example, workspace `\"my-api\"` while project_slug is `\"-home-user-myapp\"`.\n\n**Consequence for navigation:**\n- **Directory-first lookup** — when workspace matches the project_slug, all sessions for that workspace live under `$CONTEXT_INTELLIGENCE_ROOT\u002F{workspace}\u002Fsessions\u002F`. This is fast and the common case.\n- **Field-based filtering** — when workspace was set explicitly (overriding the slug default), scan across all project directories and filter records by `jq 'select(.workspace == \"TARGET\")'`.\n\nAlways check both: attempt directory lookup first, then fall back to cross-project field scan.\n\n---\n\n## Project Slug Algorithm\n\nThe project slug is derived from the **full absolute path** of the working directory:\n\n1. Take the resolved absolute path of `working_dir`\n2. Replace every `\u002F` with `-` and every `\\` with `-`\n3. Remove `:` (Windows drive letters)\n4. If the result does not start with `-`, prepend `-`\n5. Use `\"default\"` if the result is empty\n\nExamples:\n\n| Working Directory | Slug |\n|-------------------|------|\n| `\u002Fworkspace` | `-workspace` |\n| `\u002Fhome\u002Fuser\u002Fmy-api` | `-home-user-my-api` |\n| `\u002Fhome\u002Fuser\u002Frepos\u002Famplifier-core` | `-home-user-repos-amplifier-core` |\n\n> Note: the slug encodes the **full path**, not just the basename. `\u002Fhome\u002Falice\u002Fmyapp` and `\u002Fhome\u002Fbob\u002Fmyapp` get different slugs: `-home-alice-myapp` and `-home-bob-myapp`.\n\n---\n\n## Safe Extraction Discipline\n\nSession event files can contain lines with 100k+ tokens (e.g., `llm:response` with full model output). Four golden rules protect against context overflow:\n\n1. **Never `cat` an events.jsonl file.** A single line can be larger than your entire context window. Always use targeted extraction.\n\n2. **Use `jq -c` for structured queries.** The `-c` flag keeps output compact (one line per result). Always filter to specific fields rather than dumping entire records.\n\n3. **Use `grep -n | cut` for line-targeted extraction.** First find matching line numbers with `grep -n`, then extract specific lines with `sed` or `head`\u002F`tail`. Never pipe raw grep output of event data into your context.\n\n4. **Preview with `wc -l` and `head` before extracting.** Always check file size and peek at the first few lines before running any extraction. This prevents accidentally pulling in massive files.\n\n---\n\n## Common Navigation Patterns\n\nResolve the root once before all discovery snippets in this section:\n\n```bash\nCONTEXT_INTELLIGENCE_ROOT=\"${AMPLIFIER_CONTEXT_INTELLIGENCE_BASE_PATH:-$HOME\u002F.amplifier\u002Fprojects}\"\n```\n\n### Resolve workspace to a project directory\n\n```bash\n# If workspace == project_slug (common default), sessions are here:\nls \"$CONTEXT_INTELLIGENCE_ROOT\"\u002F{workspace}\u002Fsessions\u002F\n\n# If workspace was set explicitly and differs from project_slug,\n# find all directories containing sessions tagged with this workspace:\ngrep -rl '\"workspace\":\"{workspace}\"' \"$CONTEXT_INTELLIGENCE_ROOT\"\u002F*\u002Fsessions\u002F*\u002Fcontext-intelligence\u002Fmetadata.json \\\n  | sed 's|\u002Fcontext-intelligence\u002Fmetadata.json||'\n```\n\n### List all sessions for a workspace\n\n```bash\n# Fast path: workspace matches directory name (default case)\nfor ev in \"$CONTEXT_INTELLIGENCE_ROOT\"\u002Fmy-project\u002Fsessions\u002F*\u002Fcontext-intelligence\u002Fevents.jsonl; do\n  f=\"${ev%\u002Fevents.jsonl}\u002Fmetadata.json\"   # canonical marker = events.jsonl; fields from sibling\n  jq -r '[.session_id, .status, .started_at, .agent_name \u002F\u002F \"(root)\"] | join(\"\\t\")' \"$f\" 2>\u002Fdev\u002Fnull\ndone | sort -t$'\\t' -k3\n\n# Scoped path: workspace set explicitly — scan all projects, filter by field\nfor ev in \"$CONTEXT_INTELLIGENCE_ROOT\"\u002F*\u002Fsessions\u002F*\u002Fcontext-intelligence\u002Fevents.jsonl; do\n  f=\"${ev%\u002Fevents.jsonl}\u002Fmetadata.json\"   # canonical marker = events.jsonl; fields from sibling\n  jq -r 'select(.workspace == \"my-project\") | [.session_id, .status, .started_at, .agent_name \u002F\u002F \"(root)\"] | join(\"\\t\")' \"$f\" 2>\u002Fdev\u002Fnull\ndone | sort -t$'\\t' -k3\n```\n\n### Check what workspace a session belongs to\n\n```bash\njq -r '.workspace' metadata.json\n# or from events.jsonl (first line only — safe):\nhead -1 events.jsonl | jq -r '.workspace'\n```\n\n### Filter events by workspace across a project\n\n```bash\n# Count events per workspace across all sessions in a project directory:\njq -r '.workspace' \"$CONTEXT_INTELLIGENCE_ROOT\"\u002F-home-user-myapp\u002Fsessions\u002F*\u002Fcontext-intelligence\u002Fevents.jsonl \\\n  | sort | uniq -c | sort -rn\n```\n\n### Find sessions by status within a workspace\n\n```bash\n# Within a single project directory:\nfor ev in \"$CONTEXT_INTELLIGENCE_ROOT\"\u002Fmy-project\u002Fsessions\u002F*\u002Fcontext-intelligence\u002Fevents.jsonl; do\n  f=\"${ev%\u002Fevents.jsonl}\u002Fmetadata.json\"   # canonical marker = events.jsonl; fields from sibling\n  jq -r 'select(.status == \"running\") | .session_id' \"$f\" 2>\u002Fdev\u002Fnull\ndone\n\n# Cross-project, scoped to workspace:\nfor ev in \"$CONTEXT_INTELLIGENCE_ROOT\"\u002F*\u002Fsessions\u002F*\u002Fcontext-intelligence\u002Fevents.jsonl; do\n  f=\"${ev%\u002Fevents.jsonl}\u002Fmetadata.json\"   # canonical marker = events.jsonl; fields from sibling\n  jq -r 'select(.workspace == \"my-project\" and .status == \"running\") | .session_id' \"$f\" 2>\u002Fdev\u002Fnull\ndone\n```\n\n### Event summary for a session\n\n```bash\n# Count total events\nwc -l \u003C events.jsonl\n\n# Count events by type\njq -c '.event' events.jsonl | sort | uniq -c | sort -rn\n```\n\n### Find errors in a session\n\n```bash\n# Find error event line numbers only (never output the full lines)\ngrep -n '\"event\":\"orchestrator:error\"\\|\"event\":\"tool:error\"' events.jsonl | cut -d: -f1\n```\n\n### Extract a specific event by line number\n\n```bash\nsed -n '42p' events.jsonl | jq -c '{event, workspace, ts: .timestamp}'\n```\n\n### Count events by type in a session\n\n```bash\ngrep -c '\"event\":\"tool:pre\"' events.jsonl\n```\n\n---\n\n## Event Name Taxonomy\n\nAll events follow the `{namespace}:{action}` naming convention:\n\n| Namespace | Events | Description |\n|-----------|--------|-------------|\n| `session` | `start`, `fork`, `end` | Session lifecycle |\n| `prompt` | `submit` | User prompt submission |\n| `provider` | `request`, `response` | Provider API calls |\n| `llm` | `request`, `response` | LLM inference |\n| `tool` | `pre`, `post`, `error` | Tool execution lifecycle |\n| `orchestrator` | `start`, `complete`, `error` | Orchestrator run lifecycle |\n| `context` | `compaction` | Context window management |\n| `cancel` | `requested`, `completed` | Cancellation lifecycle |\n| `recipe` | `start`, `step`, `complete`, `approval`, `loop_iteration`, `loop_complete` | Recipe orchestration |\n| `delegate` | `agent_spawned`, `agent_completed`, `context_inherited`, `session_resumed` | Agent delegation |\n\nFor the complete field reference for each event, see `context\u002Fevent-schema.md`.\n",{"data":32,"body":34},{"name":4,"description":6,"version":33,"license":23},"0.2.0",{"type":35,"children":36},"root",[37,45,90,111,115,122,127,205,215,340,345,354,489,510,513,519,538,687,818,849,852,857,885,892,1127,1133,1276,1281,1286,1555,1560,1965,1968,1974,1998,2074,2116,2124,2162,2167,2170,2176,2188,2276,2281,2366,2411,2414,2420,2433,2549,2552,2558,2563,2620,2626,2792,2798,3198,3204,3290,3296,3402,3408,3721,3727,3839,3845,3908,3914,3974,3980,4015,4018,4024,4036,4433,4444],{"type":38,"tag":39,"props":40,"children":41},"element","h1",{"id":4},[42],{"type":43,"value":44},"text","Context Intelligence Session Navigation",{"type":38,"tag":46,"props":47,"children":48},"p",{},[49,51,58,60,66,68,74,75,81,82,88],{"type":43,"value":50},"This skill covers navigation of flat JSONL session files written by the ",{"type":38,"tag":52,"props":53,"children":55},"code",{"className":54},[],[56],{"type":43,"value":57},"LoggingHandler",{"type":43,"value":59},". 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lifecycle",{"type":38,"tag":696,"props":4328,"children":4329},{},[4330,4339,4381],{"type":38,"tag":723,"props":4331,"children":4332},{},[4333],{"type":38,"tag":52,"props":4334,"children":4336},{"className":4335},[],[4337],{"type":43,"value":4338},"recipe",{"type":38,"tag":723,"props":4340,"children":4341},{},[4342,4347,4348,4354,4355,4360,4361,4367,4368,4374,4375],{"type":38,"tag":52,"props":4343,"children":4345},{"className":4344},[],[4346],{"type":43,"value":4082},{"type":43,"value":67},{"type":38,"tag":52,"props":4349,"children":4351},{"className":4350},[],[4352],{"type":43,"value":4353},"step",{"type":43,"value":67},{"type":38,"tag":52,"props":4356,"children":4358},{"className":4357},[],[4359],{"type":43,"value":4257},{"type":43,"value":67},{"type":38,"tag":52,"props":4362,"children":4364},{"className":4363},[],[4365],{"type":43,"value":4366},"approval",{"type":43,"value":67},{"type":38,"tag":52,"props":4369,"children":4371},{"className":4370},[],[4372],{"type":43,"value":4373},"loop_iteration",{"type":43,"value":67},{"type":38,"tag":52,"props":4376,"children":4378},{"className":4377},[],[4379],{"type":43,"value":4380},"loop_complete",{"type":38,"tag":723,"props":4382,"children":4383},{},[4384],{"type":43,"value":4385},"Recipe orchestration",{"type":38,"tag":696,"props":4387,"children":4388},{},[4389,4398,4428],{"type":38,"tag":723,"props":4390,"children":4391},{},[4392],{"type":38,"tag":52,"props":4393,"children":4395},{"className":4394},[],[4396],{"type":43,"value":4397},"delegate",{"type":38,"tag":723,"props":4399,"children":4400},{},[4401,4407,4408,4414,4415,4421,4422],{"type":38,"tag":52,"props":4402,"children":4404},{"className":4403},[],[4405],{"type":43,"value":4406},"agent_spawned",{"type":43,"value":67},{"type":38,"tag":52,"props":4409,"children":4411},{"className":4410},[],[4412],{"type":43,"value":4413},"agent_completed",{"type":43,"value":67},{"type":38,"tag":52,"props":4416,"children":4418},{"className":4417},[],[4419],{"type":43,"value":4420},"context_inherited",{"type":43,"value":67},{"type":38,"tag":52,"props":4423,"children":4425},{"className":4424},[],[4426],{"type":43,"value":4427},"session_resumed",{"type":38,"tag":723,"props":4429,"children":4430},{},[4431],{"type":43,"value":4432},"Agent delegation",{"type":38,"tag":46,"props":4434,"children":4435},{},[4436,4438,4443],{"type":43,"value":4437},"For the complete field reference for each event, see ",{"type":38,"tag":52,"props":4439,"children":4441},{"className":4440},[],[4442],{"type":43,"value":100},{"type":43,"value":110},{"type":38,"tag":4445,"props":4446,"children":4447},"style",{},[4448],{"type":43,"value":4449},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":4451,"total":2698},[4452,4466,4481,4494,4500,4516],{"slug":4453,"name":4453,"fn":4454,"description":4455,"org":4456,"tags":4457,"stars":20,"repoUrl":21,"updatedAt":4465},"blob-reading","extract fields from blob URIs","Safe resolution of ci-blob:\u002F\u002F URIs — extract specific fields without dumping full payloads",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4458,4461,4464],{"name":4459,"slug":4460,"type":15},"Data Engineering","data-engineering",{"name":4462,"slug":4463,"type":15},"File Storage","file-storage",{"name":9,"slug":8,"type":15},"2026-07-07T06:52:39.196485",{"slug":4467,"name":4467,"fn":4468,"description":4469,"org":4470,"tags":4471,"stars":20,"repoUrl":21,"updatedAt":4480},"context-intelligence-evaluation-methodology","design evaluation metrics for tool signals","Use when deciding how to measure a context-intelligence tool signal — metric design across quality\u002Fefficiency\u002Fefficacy axes, artifact-metric avoidance via precursor measurement, A\u002FB and statistical-N discipline, and test-data fidelity.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4472,4473,4476,4477],{"name":13,"slug":14,"type":15},{"name":4474,"slug":4475,"type":15},"Evals","evals",{"name":9,"slug":8,"type":15},{"name":4478,"slug":4479,"type":15},"Statistics","statistics","2026-07-07T06:52:41.770083",{"slug":4482,"name":4482,"fn":4483,"description":4484,"org":4485,"tags":4486,"stars":20,"repoUrl":21,"updatedAt":4493},"context-intelligence-graph-query","query context intelligence property graphs","Use when querying the context-intelligence property graph for session history, tool call traces, LLM iteration analysis, execution scale metrics, agent delegation trees, skill loading, and recipe orchestration. Covers all graph layers, cross-layer SOURCED_FROM joins, SST navigation, blob handling, and verified Cypher patterns.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4487,4488,4489,4492],{"name":18,"slug":19,"type":15},{"name":13,"slug":14,"type":15},{"name":4490,"slug":4491,"type":15},"Graph Analysis","graph-analysis",{"name":9,"slug":8,"type":15},"2026-07-07T06:52:37.897652",{"slug":4,"name":4,"fn":5,"description":6,"org":4495,"tags":4496,"stars":20,"repoUrl":21,"updatedAt":22},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4497,4498,4499],{"name":18,"slug":19,"type":15},{"name":13,"slug":14,"type":15},{"name":9,"slug":8,"type":15},{"slug":4501,"name":4501,"fn":4502,"description":4503,"org":4504,"tags":4505,"stars":20,"repoUrl":21,"updatedAt":4515},"context-intelligence-session-reconstruction","reconstruct local Amplifier session files","Reconstruct local Amplifier session files from the context-intelligence graph server — events.jsonl, transcript.jsonl, and metadata.json",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4506,4508,4511,4512],{"name":4507,"slug":190,"type":15},"Amplifier",{"name":4509,"slug":4510,"type":15},"Metadata","metadata",{"name":9,"slug":8,"type":15},{"name":4513,"slug":4514,"type":15},"Observability","observability","2026-07-03T16:31:03.605475",{"slug":4517,"name":4517,"fn":4518,"description":4519,"org":4520,"tags":4521,"stars":20,"repoUrl":21,"updatedAt":4530},"workflow-pattern-analysis","analyze workflow success and failure patterns","Analyse failure and success patterns across many runs of a specific workflow using context-intelligence session data. Use when you want to answer: \"How is \u003Cworkflow> failing?\", \"What does a successful run look like vs a failing one?\", \"Which steps are the most common failure points?\", or \"What patterns appear consistently across sessions?\" Triggers on: workflow failure patterns, session failure analysis, compare successful and failing runs, what patterns appear across sessions, session behaviour investigation, how is the workflow failing, success patterns, failure signals, identify session signals.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4522,4523,4526,4527],{"name":13,"slug":14,"type":15},{"name":4524,"slug":4525,"type":15},"Debugging","debugging",{"name":9,"slug":8,"type":15},{"name":4528,"slug":4529,"type":15},"Workflow Automation","workflow-automation","2026-07-07T06:52:43.061859",{"items":4532,"total":4722},[4533,4555,4573,4592,4607,4624,4635,4648,4663,4678,4697,4710],{"slug":4534,"name":4534,"fn":4535,"description":4536,"org":4537,"tags":4538,"stars":4552,"repoUrl":4553,"updatedAt":4554},"rushstack-best-practices","manage Rush monorepos with best practices","Provides best practices and guidance for working with Rush monorepos. Use when the user is working in a Rush-based repository, asks about Rush commands (install, update, build, rebuild), needs help with project selection, dependency management, build caching, subspace configuration, or troubleshooting Rush-specific issues.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4539,4542,4545,4546,4549],{"name":4540,"slug":4541,"type":15},"Engineering","engineering",{"name":4543,"slug":4544,"type":15},"Local Development","local-development",{"name":9,"slug":8,"type":15},{"name":4547,"slug":4548,"type":15},"Project Management","project-management",{"name":4550,"slug":4551,"type":15},"Rush","rush",6484,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frushstack","2026-04-06T18:34:44.965032",{"slug":4556,"name":4556,"fn":4557,"description":4558,"org":4559,"tags":4560,"stars":4570,"repoUrl":4571,"updatedAt":4572},"azure-ai-agents-persistent-dotnet","build AI agents with Azure .NET SDK","Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: \"PersistentAgentsClient\", \"persistent agents\", \"agent threads\", \"agent runs\", \"streaming agents\", \"function calling agents .NET\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4561,4564,4565,4568],{"name":4562,"slug":4563,"type":15},".NET","net",{"name":18,"slug":19,"type":15},{"name":4566,"slug":4567,"type":15},"Azure","azure",{"name":4569,"slug":4172,"type":15},"LLM",2804,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills","2026-07-03T16:32:10.297433",{"slug":4574,"name":4574,"fn":4575,"description":4576,"org":4577,"tags":4578,"stars":4570,"repoUrl":4571,"updatedAt":4591},"azure-ai-anomalydetector-java","build anomaly detection applications with Java","Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate\u002Fmultivariate anomaly detection, time-series analysis, or AI-powered monitoring.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4579,4582,4583,4584,4587,4588],{"name":4580,"slug":4581,"type":15},"Analytics","analytics",{"name":4566,"slug":4567,"type":15},{"name":13,"slug":14,"type":15},{"name":4585,"slug":4586,"type":15},"Java","java",{"name":9,"slug":8,"type":15},{"name":4589,"slug":4590,"type":15},"Monitoring","monitoring","2026-05-13T06:14:16.261754",{"slug":4593,"name":4593,"fn":4594,"description":4595,"org":4596,"tags":4597,"stars":4570,"repoUrl":4571,"updatedAt":4606},"azure-ai-contentsafety-java","build content moderation applications with Azure AI","Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text\u002Fimage analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4598,4601,4602,4603],{"name":4599,"slug":4600,"type":15},"AI Infrastructure","ai-infrastructure",{"name":4566,"slug":4567,"type":15},{"name":4585,"slug":4586,"type":15},{"name":4604,"slug":4605,"type":15},"Security","security","2026-07-07T06:53:31.293235",{"slug":4608,"name":4608,"fn":4609,"description":4610,"org":4611,"tags":4612,"stars":4570,"repoUrl":4571,"updatedAt":4623},"azure-ai-contentsafety-py","detect harmful content with Azure AI Content Safety","Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.\nTriggers: \"azure-ai-contentsafety\", \"ContentSafetyClient\", \"content moderation\", \"harmful content\", \"text analysis\", \"image analysis\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4613,4614,4617,4618,4619,4622],{"name":4566,"slug":4567,"type":15},{"name":4615,"slug":4616,"type":15},"Compliance","compliance",{"name":4569,"slug":4172,"type":15},{"name":9,"slug":8,"type":15},{"name":4620,"slug":4621,"type":15},"Python","python",{"name":4604,"slug":4605,"type":15},"2026-07-18T05:14:23.017504",{"slug":4625,"name":4625,"fn":4626,"description":4627,"org":4628,"tags":4629,"stars":4570,"repoUrl":4571,"updatedAt":4634},"azure-ai-language-conversations-py","implement conversational language understanding with Python","Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4630,4631,4632,4633],{"name":4580,"slug":4581,"type":15},{"name":4566,"slug":4567,"type":15},{"name":4569,"slug":4172,"type":15},{"name":4620,"slug":4621,"type":15},"2026-07-31T05:54:29.068751",{"slug":4636,"name":4636,"fn":4637,"description":4638,"org":4639,"tags":4640,"stars":4570,"repoUrl":4571,"updatedAt":4647},"azure-ai-translation-text-py","translate text using Azure AI services","Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.\nTriggers: \"text translation\", \"translator\", \"translate text\", \"transliterate\", \"TextTranslationClient\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4641,4644,4645,4646],{"name":4642,"slug":4643,"type":15},"API Development","api-development",{"name":4566,"slug":4567,"type":15},{"name":9,"slug":8,"type":15},{"name":4620,"slug":4621,"type":15},"2026-07-18T05:14:16.988376",{"slug":4649,"name":4649,"fn":4650,"description":4651,"org":4652,"tags":4653,"stars":4570,"repoUrl":4571,"updatedAt":4662},"azure-ai-vision-imageanalysis-py","analyze images with Azure AI Vision","Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding tasks.\nTriggers: \"image analysis\", \"computer vision\", \"OCR\", \"object detection\", \"ImageAnalysisClient\", \"image caption\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4654,4655,4658,4661],{"name":4566,"slug":4567,"type":15},{"name":4656,"slug":4657,"type":15},"Computer Vision","computer-vision",{"name":4659,"slug":4660,"type":15},"Images","images",{"name":4620,"slug":4621,"type":15},"2026-07-18T05:14:18.007737",{"slug":4664,"name":4664,"fn":4665,"description":4666,"org":4667,"tags":4668,"stars":4570,"repoUrl":4571,"updatedAt":4677},"azure-appconfiguration-java","manage configuration with Azure App Configuration","Azure App Configuration SDK for Java. Centralized application configuration management with key-value settings, feature flags, and snapshots.\nTriggers: \"ConfigurationClient java\", \"app configuration java\", \"feature flag java\", \"configuration setting java\", \"azure config java\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4669,4670,4673,4676],{"name":4566,"slug":4567,"type":15},{"name":4671,"slug":4672,"type":15},"Configuration","configuration",{"name":4674,"slug":4675,"type":15},"Feature Flags","feature-flags",{"name":4585,"slug":4586,"type":15},"2026-07-03T16:32:01.278468",{"slug":4679,"name":4679,"fn":4680,"description":4681,"org":4682,"tags":4683,"stars":4570,"repoUrl":4571,"updatedAt":4696},"azure-cosmos-rust","build applications with Azure Cosmos DB","Azure Cosmos DB library for Rust (NoSQL API). Document CRUD, containers, and globally distributed data.\nTriggers: \"cosmos db rust\", \"CosmosClient rust\", \"document crud rust\", \"NoSQL rust\", \"partition key rust\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4684,4687,4690,4693],{"name":4685,"slug":4686,"type":15},"Cosmos DB","cosmos-db",{"name":4688,"slug":4689,"type":15},"Database","database",{"name":4691,"slug":4692,"type":15},"NoSQL","nosql",{"name":4694,"slug":4695,"type":15},"Rust","rust","2026-07-31T05:54:27.021432",{"slug":4698,"name":4698,"fn":4680,"description":4699,"org":4700,"tags":4701,"stars":4570,"repoUrl":4571,"updatedAt":4709},"azure-cosmos-ts","Azure Cosmos DB JavaScript\u002FTypeScript SDK (@azure\u002Fcosmos) for data plane operations. Use for CRUD operations on documents, queries, bulk operations, and container management. Triggers: \"Cosmos DB\", \"@azure\u002Fcosmos\", \"CosmosClient\", \"document CRUD\", \"NoSQL queries\", \"bulk operations\", \"partition key\", \"container.items\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4702,4703,4704,4705,4706],{"name":4685,"slug":4686,"type":15},{"name":4688,"slug":4689,"type":15},{"name":9,"slug":8,"type":15},{"name":4691,"slug":4692,"type":15},{"name":4707,"slug":4708,"type":15},"TypeScript","typescript","2026-07-03T16:31:19.368382",{"slug":4711,"name":4711,"fn":4712,"description":4713,"org":4714,"tags":4715,"stars":4570,"repoUrl":4571,"updatedAt":4721},"azure-data-tables-java","build table storage applications with Java","Build table storage applications with Azure Tables SDK for Java. Use when working with Azure Table Storage or Cosmos DB Table API for NoSQL key-value data, schemaless storage, or structured data at scale.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[4716,4717,4718,4719,4720],{"name":4566,"slug":4567,"type":15},{"name":4685,"slug":4686,"type":15},{"name":4688,"slug":4689,"type":15},{"name":4585,"slug":4586,"type":15},{"name":4691,"slug":4692,"type":15},"2026-05-13T06:14:17.582229",267]