[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-aws-labs-aidlc-session-cost":3,"mdc--f6retd-key":34,"related-repo-aws-labs-aidlc-session-cost":403,"related-org-aws-labs-aidlc-session-cost":498},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":12,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":29,"sourceUrl":32,"mdContent":33},"aidlc-session-cost","monitor AI-DLC workflow session costs","Read-only session cost view. Prints deterministic aggregates for the current workflow — duration, stage outcomes, memory entries, sensor firings, learnings captured — sourced entirely from `aidlc-runtime.ts summary`. Never mutates workflow state, never emits audit events, never writes files.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},"aws-labs","AWS Labs","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Faws-labs.png","awslabs",[13,17,20],{"name":14,"slug":15,"type":16},"Observability","observability","tag",{"name":18,"slug":19,"type":16},"Reporting","reporting",{"name":21,"slug":22,"type":16},"Cost Optimization","cost-optimization",4261,"https:\u002F\u002Fgithub.com\u002Fawslabs\u002Faidlc-workflows","2026-09-02T07:47:33.662356",null,754,[],{"repoUrl":24,"stars":23,"forks":27,"topics":30,"description":31},[],"AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI coding agents","https:\u002F\u002Fgithub.com\u002Fawslabs\u002Faidlc-workflows\u002Ftree\u002FHEAD\u002Fcore\u002Fskills\u002Faidlc-session-cost","---\nname: aidlc-session-cost\ndescription: >\n  Read-only session cost view. Prints deterministic aggregates for the\n  current workflow — duration, stage outcomes, memory entries, sensor\n  firings, learnings captured — sourced entirely from\n  `aidlc-runtime.ts summary`. Never mutates workflow state, never emits\n  audit events, never writes files.\nargument-hint: \"\"\nuser-invocable: true\nclassification: read-only\n---\n\n# AI-DLC Session Cost\n\n## Purpose\n\nGive the team a transparent, deterministic view of what the current\nworkflow has consumed: how long it has run, how many stages have\ncleared their gates, how much the orchestrator wrote to its observation\ndiaries, how often sensors fired, and how many learnings were captured.\n\nEvery number this skill prints comes from\n`bun {{HARNESS_DIR}}\u002Ftools\u002Faidlc-runtime.ts summary --json` — the materialised,\nevent-sourced view over `runtime-graph.json`. This skill does **no\ncounting of its own**. It does not estimate tokens, does not walk the\nartefact tree, and does not read `audit.md`. If a number isn't in the\ntool's output, this skill does not invent it.\n\n## Classification\n\nRead-only. This skill never advances the workflow stage pointer, never\nemits an audit event, and never writes a file. It is safe to run at any\npoint in a workflow, including mid-stage.\n\n## Steps\n\n### Step 1: Read the aggregates\n\nRun:\n\n```bash\nbun {{HARNESS_DIR}}\u002Ftools\u002Faidlc-runtime.ts summary --json\n```\n\nIf the command exits non-zero (no `runtime-graph.json` yet — the\nworkflow hasn't compiled a graph), print:\n\n```\nNo session data yet.\n\nSession cost becomes available once a workflow has started and its\nfirst stage transition has compiled runtime-graph.json. Run \u002Faidlc to\nbegin, then re-run \u002Faidlc-session-cost.\n```\n\nand STOP.\n\nOtherwise parse the JSON. The shape is:\n\n```jsonc\n{\n  \"workflow_id\": \"...\",          \u002F\u002F ISO timestamp of the live workflow\n  \"scope\": \"...\",\n  \"started_at\": \"...\",\n  \"duration_minutes\": 40,         \u002F\u002F null when nothing has completed yet\n  \"stages\":   { \"total\": N, \"approved\": N, \"failed\": N, \"pending\": N },\n  \"by_phase\": { \"\u003Cphase>\": { \"total\": N, \"approved\": N, \"failed\": N, \"pending\": N }, ... },\n  \"memory\":   { \"total\": N, \"interpretations\": N, \"deviations\": N, \"tradeoffs\": N, \"open_questions\": N },\n  \"sensors\":  { \"total\": N, \"passed\": N, \"failed\": N, \"budget_override\": N, \"incomplete\": N },\n  \"learnings\":{ \"from_orchestrator\": N, \"from_user_addition\": N }\n}\n```\n\n### Step 2: Render the report\n\nPrint the fields verbatim — do not recompute, round, or re-estimate any\nvalue. Use `in progress` when `duration_minutes` is `null`.\n\n```\nSession Cost\n============\n\nWorkflow:   {workflow_id}\nScope:      {scope}\nDuration:   {duration_minutes} min   (or \"in progress\")\n\nStages\n  Total:      {stages.total}\n  Approved:   {stages.approved}\n  Failed:     {stages.failed}\n  Pending:    {stages.pending}\n\nBy phase\n  {phase}    {approved}\u002F{total} approved[, {failed} failed][, {pending} pending]\n  ...\n\nMemory entries\n  Total:            {memory.total}\n  Interpretations:  {memory.interpretations}\n  Deviations:       {memory.deviations}\n  Trade-offs:       {memory.tradeoffs}\n  Open questions:   {memory.open_questions}\n\nSensors\n  Fired:            {sensors.total}\n  Passed:           {sensors.passed}\n  Failed:           {sensors.failed}\n  Budget-override:  {sensors.budget_override}\n  Incomplete:       {sensors.incomplete}\n\nLearnings captured\n  From orchestrator:    {learnings.from_orchestrator}\n  From user additions:  {learnings.from_user_addition}\n```\n\n### Step 3: Surface advisory notes (optional, narrative only)\n\nYou may add a short narrative note after the table — for example,\nflagging that many stages are still pending, or that sensors are firing\n`incomplete` often. Keep it to one or two sentences and base it only on\nthe numbers above. Do not invent metrics the tool did not report.\n\n> Note on tokens: this skill deliberately does **not** print a token\n> estimate. The retired file-size-to-token heuristic was guesswork\n> dressed as data. If you need real token accounting, read it from your\n> Claude Code session, not from a file-size approximation.\n",{"data":35,"body":39},{"name":4,"description":6,"argument-hint":36,"user-invocable":37,"classification":38},"",true,"read-only",{"type":40,"children":41},"root",[42,51,58,64,102,108,113,119,126,131,169,181,191,196,201,318,324,353,362,368,381,397],{"type":43,"tag":44,"props":45,"children":47},"element","h1",{"id":46},"ai-dlc-session-cost",[48],{"type":49,"value":50},"text","AI-DLC Session Cost",{"type":43,"tag":52,"props":53,"children":55},"h2",{"id":54},"purpose",[56],{"type":49,"value":57},"Purpose",{"type":43,"tag":59,"props":60,"children":61},"p",{},[62],{"type":49,"value":63},"Give the team a transparent, deterministic view of what the current\nworkflow has consumed: how long it has run, how many stages have\ncleared their gates, how much the orchestrator wrote to its observation\ndiaries, how often sensors fired, and how many learnings were captured.",{"type":43,"tag":59,"props":65,"children":66},{},[67,69,76,78,84,86,92,94,100],{"type":49,"value":68},"Every number this skill prints comes from\n",{"type":43,"tag":70,"props":71,"children":73},"code",{"className":72},[],[74],{"type":49,"value":75},"bun {{HARNESS_DIR}}\u002Ftools\u002Faidlc-runtime.ts summary --json",{"type":49,"value":77}," — the materialised,\nevent-sourced view over ",{"type":43,"tag":70,"props":79,"children":81},{"className":80},[],[82],{"type":49,"value":83},"runtime-graph.json",{"type":49,"value":85},". This skill does ",{"type":43,"tag":87,"props":88,"children":89},"strong",{},[90],{"type":49,"value":91},"no\ncounting of its own",{"type":49,"value":93},". It does not estimate tokens, does not walk the\nartefact tree, and does not read ",{"type":43,"tag":70,"props":95,"children":97},{"className":96},[],[98],{"type":49,"value":99},"audit.md",{"type":49,"value":101},". If a number isn't in the\ntool's output, this skill does not invent it.",{"type":43,"tag":52,"props":103,"children":105},{"id":104},"classification",[106],{"type":49,"value":107},"Classification",{"type":43,"tag":59,"props":109,"children":110},{},[111],{"type":49,"value":112},"Read-only. This skill never advances the workflow stage pointer, never\nemits an audit event, and never writes a file. 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Run \u002Faidlc to\nbegin, then re-run \u002Faidlc-session-cost.\n",[187],{"type":43,"tag":70,"props":188,"children":189},{"__ignoreMap":36},[190],{"type":49,"value":185},{"type":43,"tag":59,"props":192,"children":193},{},[194],{"type":49,"value":195},"and STOP.",{"type":43,"tag":59,"props":197,"children":198},{},[199],{"type":49,"value":200},"Otherwise parse the JSON. The shape is:",{"type":43,"tag":132,"props":202,"children":206},{"className":203,"code":204,"language":205,"meta":36,"style":36},"language-jsonc shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","{\n  \"workflow_id\": \"...\",          \u002F\u002F ISO timestamp of the live workflow\n  \"scope\": \"...\",\n  \"started_at\": \"...\",\n  \"duration_minutes\": 40,         \u002F\u002F null when nothing has completed yet\n  \"stages\":   { \"total\": N, \"approved\": N, \"failed\": N, \"pending\": N },\n  \"by_phase\": { \"\u003Cphase>\": { \"total\": N, \"approved\": N, \"failed\": N, \"pending\": N }, ... },\n  \"memory\":   { \"total\": N, \"interpretations\": N, \"deviations\": N, \"tradeoffs\": N, \"open_questions\": N },\n  \"sensors\":  { \"total\": N, \"passed\": N, \"failed\": N, \"budget_override\": N, \"incomplete\": N },\n  \"learnings\":{ \"from_orchestrator\": N, \"from_user_addition\": N }\n}\n","jsonc",[207],{"type":43,"tag":70,"props":208,"children":209},{"__ignoreMap":36},[210,218,232,241,250,264,273,282,291,300,309],{"type":43,"tag":142,"props":211,"children":212},{"class":144,"line":145},[213],{"type":43,"tag":142,"props":214,"children":215},{},[216],{"type":49,"value":217},"{\n",{"type":43,"tag":142,"props":219,"children":221},{"class":144,"line":220},2,[222,227],{"type":43,"tag":142,"props":223,"children":224},{},[225],{"type":49,"value":226},"  \"workflow_id\": \"...\",",{"type":43,"tag":142,"props":228,"children":229},{},[230],{"type":49,"value":231},"          \u002F\u002F ISO timestamp of the live workflow\n",{"type":43,"tag":142,"props":233,"children":235},{"class":144,"line":234},3,[236],{"type":43,"tag":142,"props":237,"children":238},{},[239],{"type":49,"value":240},"  \"scope\": \"...\",\n",{"type":43,"tag":142,"props":242,"children":244},{"class":144,"line":243},4,[245],{"type":43,"tag":142,"props":246,"children":247},{},[248],{"type":49,"value":249},"  \"started_at\": \"...\",\n",{"type":43,"tag":142,"props":251,"children":253},{"class":144,"line":252},5,[254,259],{"type":43,"tag":142,"props":255,"children":256},{},[257],{"type":49,"value":258},"  \"duration_minutes\": 40,",{"type":43,"tag":142,"props":260,"children":261},{},[262],{"type":49,"value":263},"         \u002F\u002F null when nothing has completed yet\n",{"type":43,"tag":142,"props":265,"children":267},{"class":144,"line":266},6,[268],{"type":43,"tag":142,"props":269,"children":270},{},[271],{"type":49,"value":272},"  \"stages\":   { \"total\": N, \"approved\": N, \"failed\": N, \"pending\": N },\n",{"type":43,"tag":142,"props":274,"children":276},{"class":144,"line":275},7,[277],{"type":43,"tag":142,"props":278,"children":279},{},[280],{"type":49,"value":281},"  \"by_phase\": { \"\u003Cphase>\": { \"total\": N, \"approved\": N, \"failed\": N, \"pending\": N }, ... },\n",{"type":43,"tag":142,"props":283,"children":285},{"class":144,"line":284},8,[286],{"type":43,"tag":142,"props":287,"children":288},{},[289],{"type":49,"value":290},"  \"memory\":   { \"total\": N, \"interpretations\": N, \"deviations\": N, \"tradeoffs\": N, \"open_questions\": N },\n",{"type":43,"tag":142,"props":292,"children":294},{"class":144,"line":293},9,[295],{"type":43,"tag":142,"props":296,"children":297},{},[298],{"type":49,"value":299},"  \"sensors\":  { \"total\": N, \"passed\": N, \"failed\": N, \"budget_override\": N, \"incomplete\": N },\n",{"type":43,"tag":142,"props":301,"children":303},{"class":144,"line":302},10,[304],{"type":43,"tag":142,"props":305,"children":306},{},[307],{"type":49,"value":308},"  \"learnings\":{ \"from_orchestrator\": N, \"from_user_addition\": N }\n",{"type":43,"tag":142,"props":310,"children":312},{"class":144,"line":311},11,[313],{"type":43,"tag":142,"props":314,"children":315},{},[316],{"type":49,"value":317},"}\n",{"type":43,"tag":120,"props":319,"children":321},{"id":320},"step-2-render-the-report",[322],{"type":49,"value":323},"Step 2: Render the report",{"type":43,"tag":59,"props":325,"children":326},{},[327,329,335,337,343,345,351],{"type":49,"value":328},"Print the fields verbatim — do not recompute, round, or re-estimate any\nvalue. Use ",{"type":43,"tag":70,"props":330,"children":332},{"className":331},[],[333],{"type":49,"value":334},"in progress",{"type":49,"value":336}," when ",{"type":43,"tag":70,"props":338,"children":340},{"className":339},[],[341],{"type":49,"value":342},"duration_minutes",{"type":49,"value":344}," is ",{"type":43,"tag":70,"props":346,"children":348},{"className":347},[],[349],{"type":49,"value":350},"null",{"type":49,"value":352},".",{"type":43,"tag":132,"props":354,"children":357},{"className":355,"code":356,"language":49},[184],"Session Cost\n============\n\nWorkflow:   {workflow_id}\nScope:      {scope}\nDuration:   {duration_minutes} min   (or \"in progress\")\n\nStages\n  Total:      {stages.total}\n  Approved:   {stages.approved}\n  Failed:     {stages.failed}\n  Pending:    {stages.pending}\n\nBy phase\n  {phase}    {approved}\u002F{total} approved[, {failed} failed][, {pending} pending]\n  ...\n\nMemory entries\n  Total:            {memory.total}\n  Interpretations:  {memory.interpretations}\n  Deviations:       {memory.deviations}\n  Trade-offs:       {memory.tradeoffs}\n  Open questions:   {memory.open_questions}\n\nSensors\n  Fired:            {sensors.total}\n  Passed:           {sensors.passed}\n  Failed:           {sensors.failed}\n  Budget-override:  {sensors.budget_override}\n  Incomplete:       {sensors.incomplete}\n\nLearnings captured\n  From orchestrator:    {learnings.from_orchestrator}\n  From user additions:  {learnings.from_user_addition}\n",[358],{"type":43,"tag":70,"props":359,"children":360},{"__ignoreMap":36},[361],{"type":49,"value":356},{"type":43,"tag":120,"props":363,"children":365},{"id":364},"step-3-surface-advisory-notes-optional-narrative-only",[366],{"type":49,"value":367},"Step 3: Surface advisory notes (optional, narrative only)",{"type":43,"tag":59,"props":369,"children":370},{},[371,373,379],{"type":49,"value":372},"You may add a short narrative note after the table — for example,\nflagging that many stages are still pending, or that sensors are firing\n",{"type":43,"tag":70,"props":374,"children":376},{"className":375},[],[377],{"type":49,"value":378},"incomplete",{"type":49,"value":380}," often. Keep it to one or two sentences and base it only on\nthe numbers above. Do not invent metrics the tool did not report.",{"type":43,"tag":382,"props":383,"children":384},"blockquote",{},[385],{"type":43,"tag":59,"props":386,"children":387},{},[388,390,395],{"type":49,"value":389},"Note on tokens: this skill deliberately does ",{"type":43,"tag":87,"props":391,"children":392},{},[393],{"type":49,"value":394},"not",{"type":49,"value":396}," print a token\nestimate. The retired file-size-to-token heuristic was guesswork\ndressed as data. If you need real token accounting, read it from your\nClaude Code session, not from a file-size approximation.",{"type":43,"tag":398,"props":399,"children":400},"style",{},[401],{"type":49,"value":402},"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":404,"total":284},[405,421,432,452,466,481,492],{"slug":406,"name":406,"fn":407,"description":408,"org":409,"tags":410,"stars":23,"repoUrl":24,"updatedAt":420},"aidlc","orchestrate AI-driven development lifecycle workflows","AI-DLC workflow orchestrator. Start, resume, or manage an AI-driven development lifecycle. Scopes are defined one file per scope under `.kiro\u002Fscopes\u002F`; run `bun .kiro\u002Ftools\u002Faidlc-utility.ts help` for the authoritative list and descriptions. Utilities: --status, --doctor, --stage, --phase, --scope, --depth, --test-strategy, --review, --version, --help, plus the intent and space verbs. Or describe what you want to build and the scope will be auto-detected.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[411,414,417],{"name":412,"slug":413,"type":16},"Agents","agents",{"name":415,"slug":416,"type":16},"Automation","automation",{"name":418,"slug":419,"type":16},"Workflow","workflow","2026-09-02T07:47:34.75815",{"slug":422,"name":422,"fn":423,"description":424,"org":425,"tags":426,"stars":23,"repoUrl":24,"updatedAt":431},"aidlc-jump","navigate AI-DLC workflow stages and phases","Jump the active AI-DLC workflow to a stage or phase. A Cursor-native shortcut for `\u002Faidlc --stage \u003Ctarget>` or `\u002Faidlc --phase \u003Ctarget>`.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[427,428],{"name":415,"slug":416,"type":16},{"name":429,"slug":430,"type":16},"Navigation","navigation","2026-09-02T07:48:09.505949",{"slug":433,"name":433,"fn":434,"description":435,"org":436,"tags":437,"stars":23,"repoUrl":24,"updatedAt":451},"aidlc-knowledge","index documents for AI-DLC agent citation","Index the team's own documents — PDFs, Word files, Markdown, plain text — into a per-space catalog the AI-DLC agents can cite. Wraps `aidlc-knowledge.ts`: onboard, sync, list, show, associate, dissociate, rebind, summarize. Every catalog row is written by the tool under a workspace lock; this skill never edits the catalog by hand and never advances workflow state.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[438,439,442,445,448],{"name":412,"slug":413,"type":16},{"name":440,"slug":441,"type":16},"Documents","documents",{"name":443,"slug":444,"type":16},"Knowledge Management","knowledge-management",{"name":446,"slug":447,"type":16},"Markdown","markdown",{"name":449,"slug":450,"type":16},"PDF","pdf","2026-09-02T07:48:10.614775",{"slug":453,"name":453,"fn":454,"description":455,"org":456,"tags":457,"stars":23,"repoUrl":24,"updatedAt":465},"aidlc-outcomes-pack","generate AI-DLC workflow handover documentation","Generate a comprehensive handover document at workflow close so the team can own, operate, and continue the system without re-running the workflow. Stage\u002Fphase\u002Flearning counts come from `aidlc-runtime.ts summary`; prose comes from the artefacts. Writes OUTCOMES.md but never mutates workflow state or emits audit events.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[458,461,464],{"name":459,"slug":460,"type":16},"Documentation","documentation",{"name":462,"slug":463,"type":16},"Process Documentation","process-documentation",{"name":18,"slug":19,"type":16},"2026-09-02T07:47:34.212738",{"slug":467,"name":467,"fn":468,"description":469,"org":470,"tags":471,"stars":23,"repoUrl":24,"updatedAt":480},"aidlc-replay","generate AI-DLC session narrative reports","Print a structured session narrative for stakeholders who weren't in the room. Numbers (stage counts, phase rollup, duration) come from `aidlc-runtime.ts summary`; prose comes from the audit trail and artefacts. 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