
Description
Use this skill when the user is invoking the DOCA PCC Counters tool — the `pcc_counters.sh` bash script under the DOCA tools directory — to arm and read the fixed firmware/hardware PCC (Programmable Congestion Control) diagnostic counters (CNP, RTT, WRED-drop, etc.) on a ConnectX / BlueField device via mst + the mlx5 debugfs `diag_cnt` interface. The script takes two positional args — `set | query` and an mst device path — with no `--help` or subcommands. Trigger even without "pcc_counters.sh" or "PCC counters": "how do I read the CNP / RTT / WRED-drop counters", "PCC counter stuck at zero", "the script says Bad Device", or "is congestion control dropping packets on this port?". Route elsewhere for writing a custom PCC algorithm (doca-pcc), factory firmware PCC config, DOCA install, or fleet-wide CC tuning.
SKILL.md
DOCA PCC Counters (pcc_counters.sh)
Where to start: This is a tool skill for invoking
pcc_counters.sh — a small bash script that arms and reads the
device's fixed set of firmware / hardware PCC diagnostic
counters (CNP count, RTT-perf, WRED-drop, RTT-gen, handled
events) through the mlx5 debugfs diag_cnt interface. Open
TASKS.md and start at ## run for
the canonical set-then-query sequence, or
## debug when the user reports
"ERROR: Bad Device", "counter stuck at zero", or "the
dump is empty". Open CAPABILITIES.md when
the question is which counters the script reports and how it
reaches them. If the user has not installed DOCA / MFT yet,
route to doca-setup first.
This skill is the firmware / HW PCC counter readout surface.
It is NOT the host-side control library that loads custom
congestion-control kernels onto the DPA (that is
doca-pcc) and it is NOT the
firmware PCC algorithm configuration (that path is firmware
configuration, routed via
doca-public-knowledge-map).
The counters this script reads are device / firmware
diagnostic counters that exist regardless of whether a custom
doca-pcc DPA kernel is running — do not condition them on a
custom kernel being loaded.
Example questions this skill answers well
The CLASSES of pcc_counters.sh questions this skill is built
to answer, each with one worked example. The class is the
load-bearing piece; the worked example is one instance.
- "How do I read the PCC diagnostic counters on this
device?" — worked example: "arm and dump the CNP / RTT /
WRED-drop counters for
/dev/mst/mt41692_pciconf0". Answered by the fixed counter set inCAPABILITIES.md ## Capabilities and modes- the
set-then-queryinvocation inTASKS.md ## run.
- the
- "What is the smallest legal invocation?" — worked
example: "what exactly do I type?". Answered by the
two-positional-argument contract
(
set | query+ an mst device path) inTASKS.md ## run. - "The script printed
ERROR: Bad Device— what's wrong?" — worked example: "my device path is not matching". Answered by the device-resolution layer inCAPABILITIES.md ## Error taxonomy - "A counter is stuck at zero — is the device idle, the
counters not armed, or genuinely no events?" — worked
example: "
PCC_CNP_COUNTreads 0 afterquery". Answered by the arm-before-read rule and the layered diagnosis inTASKS.md ## debug+CAPABILITIES.md ## Error taxonomy. - "Is this script on my install, and where?" — worked
example: "is
pcc_counters.shpresent and where does the install put it". Answered by the install overlay inCAPABILITIES.md ## Version compatibility, which redirects to the canonicaldoca-versionrules.
Audience
This skill serves operators, developers, and AI agents who need to read a ConnectX / BlueField device's firmware PCC diagnostic counters to reason about congestion-control behaviour (CNP generation, RTT requests/responses, WRED drops) on a port. Concretely:
- A network operator confirming whether congestion-control events (CNPs, RTT, WRED drops) are occurring on a device.
- A developer correlating a custom
doca-pccalgorithm's effect with the device-level PCC diagnostic counters (the script reads the firmware counters; the custom algorithm itself is a separate surface owned bydoca-pcc). - An AI agent producing a PCC counter snapshot as evidence for a congestion-control investigation.
It is not for users debugging the script's bash itself,
not the place to learn how to write a custom PCC
algorithm — that audience belongs in
doca-pcc — and not the
place for users who want to configure the factory firmware PCC
algorithm (route via
doca-public-knowledge-map).
pcc_counters.sh is shipped as a plain bash script
installed under the DOCA tools directory (per install_data in
tools/pcc_counters/meson.build), not a compiled binary and
not a library you link against. The skill uses the bundle's
kind: tool three-file shape (SKILL.md + CAPABILITIES.md
TASKS.md) so the agent's task-verb contract (configure / build / modify / run / test / debug) is uniform across the bundle.
When to load this skill
Load this skill when the user is — or the agent needs to — arm and read the device PCC diagnostic counters on a host or BlueField Arm with the mst tools available and debugfs mounted. Concretely:
- Arming the diagnostic counters with
seton a target mst device. - Reading the armed counters with
queryand quoting the named counter lines verbatim. - Capturing a counter readout as evidence for a congestion-control investigation.
Do not load this skill for general DOCA orientation,
custom-PCC algorithm design, the host-side doca-pcc library
API, the factory firmware PCC algorithm, or DOCA / MFT install.
For those, route to
doca-public-knowledge-map,
doca-pcc, or
doca-setup.
What this skill provides
This is a thin loader. Substantive material lives in two companion files:
CAPABILITIES.md— whatpcc_counters.shdoes: the exact two-operation surface (setarms the device's diagnostic counters by writing counter IDs + params to debugfs;queryreads thediag_cnt/dumpand prints the named counters), the FIXED firmware / HW counter set it knows (PCC_CNP_COUNT, theMAD_RTT_PERF_CONT_*, the*_EVENT_WRED_DROPfamily,HANDLED_*_EVENTS, theDROP_RTT_PORT*/RTT_GEN_PORT*families), how it resolves an mst device to a PCI address (mst status -v+lspci) and reaches/sys/kernel/debug/mlx5/<pci>/diag_cnt/, the install-availability overlay that redirects todoca-version, the layered error taxonomy (script-not-present / bad-device / not-armed-before-query / debugfs-or-permission / counter-stuck-at-zero / cross-cutting), and the safety policy that flagssetas a privileged debugfs write and any CC tuning decision derived from a reading as high-stakes.TASKS.md— step-by-step workflows for the in-scope task verbs:configure(route to install + confirm mst / debugfs / sudo),build(route to install; nothing to compile — it is a script),modify(refuse — do not patch the shipped script),run(theset-then-querysequence),test(confirm the dump contains the named counters with finite values),debug(the layered diagnosis ladder), plus aDeferred task verbsblock and aCommand appendix.
The skill assumes a host or BlueField where DOCA / MFT is
already installed (mst tools present, debugfs mounted, sudo
available) and the target device is visible to mst status -v.
What this skill deliberately does not ship
This skill is agent guidance, not a samples or scripts bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:
- Invented flags or subcommands.
pcc_counters.shhas exactly two operations (set,query), takes exactly two positional arguments, and has NO--help,--version,list,snapshot,watch, ordiff. Do not invent any. - Pre-baked example counter values. Counter values are device-, firmware-, and traffic-state-specific; a captured value will mislead an operator on a different device.
- Wrappers, parsers, or rewritten copies of the script. The script is the contract; modifying or re-implementing it is out of scope.
- A specific congestion-control tuning recommendation derived from a counter reading. That is a high-stakes domain question — the skill prescribes how to capture the counters; it refuses to translate a delta into a CC parameter change without the user's own domain analysis.
- A
samples/orreference/subtree. This is a thin loader for a documented script; substantive material lives in the script and the public PCC documentation.
Loading order
- Read this
SKILL.mdfirst to confirm the user's question is in scope (reading the device's firmware PCC diagnostic counters; not designing or loading a custom algorithm). - For what the script does, the fixed counter set, the debugfs mechanism, the install-availability overlay, the layered error surface, and the safety posture, see CAPABILITIES.md.
- For the documented invocations —
configure,build,modify,run,test,debug, plus theCommand appendix— see TASKS.md.
Related skills
doca-pcc— the host-side library for writing and loading custom congestion-control kernels onto the DPA. It is a SEPARATE surface: the firmware PCC diagnostic counterspcc_counters.shreads exist independently of any customdoca-pcckernel, but an operator tuning a custom algorithm may read these counters to observe device-level CC behaviour. Conflating the script (firmware counter readout) with the library (custom algorithm load/control) is the most common PCC first-touch error.doca-public-knowledge-map— routing to the public DOCA / PCC documentation set, including the firmware PCC algorithm configuration.doca-version— canonical DOCA version-handling rules. The## Version compatibilitysection inCAPABILITIES.mdis a concise overlay that redirects here.doca-setup— env preparation, install verification, mst tools, debugfs, and the I have no install yet path with the public NGC DOCA container. This skill assumes its preconditions are satisfied.doca-debug— the cross-cutting debug ladder. The PCC counter readout slots in as a read-only device-state evidence source before any congestion-control tuning recommendation is made.doca-programming-guide— general DOCA programming patterns shared across the bundle.
More skills from the skills repository
View all 305 skillsaccelerated-computing-cudf
accelerate data processing with cuDF
Jul 14Data AnalysisData EngineeringNVIDIAPerformanceaiq-deploy
deploy and manage NVIDIA AI-Q infrastructure
Jul 14DeploymentInfrastructureNVIDIAaiq-research
conduct deep research with AI-Q
Jul 14AgentsNVIDIAResearchamc-run-sample-calibration
run AMC sample dataset calibration
Jul 17Data AnalysisNVIDIATestingamc-run-video-calibration
calibrate video datasets with AutoMagicCalib
Jul 17AutomationImagingNVIDIAVideoamc-setup-calibration-stack
deploy AutoMagicCalib microservice with Docker
Jul 17DeploymentDockerNVIDIAOperations
More from NVIDIA
View publishernemoclaw-user-guide
retrieve NemoClaw documentation and configuration
NemoClaw
Jul 20DocumentationMCPSearchmcore-build-and-dependency
manage Megatron-LM development environments
Megatron-LM
Jul 14ContainersDeploymentPythonmcore-bump-base-image
update NVIDIA PyTorch base images
Megatron-LM
Jul 14CI/CDDeploymentmcore-cicd
manage CI/CD pipelines for Megatron-LM
Megatron-LM
Jul 14CI/CDDeploymentGitHubmcore-create-issue
investigate CI failures and create issues
Megatron-LM
Jul 14DebuggingGitHubTriagemcore-linting-and-formatting
lint and format Megatron-LM code
Megatron-LM
Jul 14Best PracticesCode Analysis