Claude Code Agent Development
anthropics/claude-plugins-official
Explains how to write agents for Claude Code plugins: the markdown file with YAML frontmatter, trigger descriptions, model and color settings, and system prompt design.
Audit an agentic software system end to end for contradictions, gaps, inconsistent contracts, capability mismatches, instruction conflicts, ambiguous results, stale documentation, unsafe lifecycle…
$ npx skills add boadij/pi-herdsman --skill agentic-system-audit -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install boadij/pi-herdsman agentic-system-audit --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/boadij/pi-herdsman.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/agentic-system-audit .claude/skills/agentic-system-audit && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "agentic-system-audit" agent skill from https://github.com/boadij/pi-herdsman/tree/main/.agents/skills/agentic-system-audit into .claude/skills/agentic-system-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentic-system-audit", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/boadij/pi-herdsman/tree/main/.agents/skills/agentic-system-auditType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add boadij/pi-herdsman --skill agentic-system-audit -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install boadij/pi-herdsman agentic-system-audit --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/boadij/pi-herdsman.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/agentic-system-audit .agents/skills/agentic-system-audit && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "agentic-system-audit" agent skill from https://github.com/boadij/pi-herdsman/tree/main/.agents/skills/agentic-system-audit into .agents/skills/agentic-system-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentic-system-audit", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add boadij/pi-herdsman --skill agentic-system-audit -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install boadij/pi-herdsman agentic-system-audit --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/boadij/pi-herdsman.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/agentic-system-audit .cursor/skills/agentic-system-audit && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "agentic-system-audit" agent skill from https://github.com/boadij/pi-herdsman/tree/main/.agents/skills/agentic-system-audit into .cursor/skills/agentic-system-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentic-system-audit", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/boadij/pi-herdsman.git --path .agents/skills/agentic-system-audit--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add boadij/pi-herdsman --skill agentic-system-audit -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install boadij/pi-herdsman agentic-system-audit --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/boadij/pi-herdsman.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/agentic-system-audit .gemini/skills/agentic-system-audit && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "agentic-system-audit" agent skill from https://github.com/boadij/pi-herdsman/tree/main/.agents/skills/agentic-system-audit into .gemini/skills/agentic-system-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentic-system-audit", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install boadij/pi-herdsman agentic-system-auditInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add boadij/pi-herdsman --skill agentic-system-audit -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/boadij/pi-herdsman.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/agentic-system-audit .github/skills/agentic-system-audit && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "agentic-system-audit" agent skill from https://github.com/boadij/pi-herdsman/tree/main/.agents/skills/agentic-system-audit into .github/skills/agentic-system-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentic-system-audit", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add boadij/pi-herdsman --skill agentic-system-audit -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install boadij/pi-herdsman agentic-system-audit --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/boadij/pi-herdsman.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/agentic-system-audit .opencode/skills/agentic-system-audit && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "agentic-system-audit" agent skill from https://github.com/boadij/pi-herdsman/tree/main/.agents/skills/agentic-system-audit into .opencode/skills/agentic-system-audit/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agentic-system-audit", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
agentic-system-auditAudit an agentic software system end to end for contradictions, gaps, inconsistent contracts, capability mismatches, instruction conflicts, ambiguous results, stale documentation, unsafe lifecycle…
Agentic System Audit is an agent skill from boadij/pi-herdsman. Audit an agentic software system end to end for contradictions, gaps, inconsistent contracts, capability mismatches, instruction conflicts, ambiguous results, stale documentation, unsafe lifecycle behavior, redundant guidance, missing enforcement, test blind spots, and architectural drift. Use when reviewing the overall health and coherence of an agent/tool system, especially systems with prompts, tools, subagents, lifecycle state, dynamic results, configuration, documentation, and multiple instruction layers.
Its SKILL.md is about 5.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows, covering Subagents. The repository describes itself as: Asynchronous Pi subagents and agent fleet orchestration for parallel coding agents with nested delegation, background work, and supervision in herdr. The licence is Apache-2.0.
8 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 3603d9f. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are json).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Agentic System Audit loads about 5.8k tokens when it runs. Until then it costs about 134 tokens; SKILL.md has 2,274 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from boadij/pi-herdsman at commit 3603d9f, republished under its Apache-2.0 licence (© boadij). 2,274 words, ~5,804 tokens.
.claude/skills/agentic-system-audit/SKILL.md (or your agent's skills folder).Audit the whole agentic contract, not isolated files.
Find where code, prompts, tools, state, results, docs, tests, configuration, packaging, or runtime capabilities disagree or leave the next safe action ambiguous.
Prefer deletion, consolidation, one canonical owner, and the smallest durable correction.
This is a read-only audit. Do not modify the repository.
Delegate the audit. The orchestrator coordinates and returns the result; it should not perform a competing repository review.
Use:
reviewer: lead auditor, evidence reconciliation, synthesis;scout: focused local evidence;researcher: external/API verification when material conclusions depend on it;implementer: never during the audit;generalist: fallback only when the required role is unavailable and its effective policy is read-only.Start with:
{ "action": "list" }Use effective capabilities from the current context. Do not assume definition-level delegation, tools, skills, or extensions survive overrides or depth.
orchestrator
└── reviewer
├── scout A: runtime/contracts/reachability
├── scout B: instructions/capabilities
├── scout C: presentation/docs/tests/package glue
└── researcher: only when the research trigger is metUse one lead reviewer. Do not spawn a second generic reviewer by default.
If the lead reviewer cannot delegate:
resultPath values to one reviewer through files;The orchestrator must not redo the scouts' analysis.
The reviewer may not receive this skill directly, so its assignment must carry the rules required for a valid audit.
Give the reviewer this objective:
Audit the repository as one agentic system. Remain strictly read-only.
Delegate three focused scouts:
- A: runtime producers, validation, state, identity, lifecycle, and production reachability;
- B: instruction ownership and effective capabilities;
- C: model/UI projections, docs, tests, and repository/package glue.
Use researcher when a candidate material finding or its impact depends on external API/runtime truth.
Before reporting any P0-P2 finding:
- identify the semantic source and relevant producers;
- prove the disputed state/value is reachable on a production path when behavior is at issue;
- trace it through every consumer boundary relevant to the claim;
- resolve material upstream/runtime assumptions for the repository's supported versions using primary evidence when available;
- verify that a claimed regression check would fail for the old behavior.
Do not report representable-but-unreachable states as defects. Do not treat differently named fields as equivalent without tracing semantics. Do not leave an answerable material uncertainty as follow-up.
If required evidence genuinely cannot be established, report a bounded
Unverified risk, not a definitive finding.Compare root/parent/child, definition/session/fork, model/UI, success/failure/recovery, configured/effective capability, and static/dynamic guidance.
Independently verify material conclusions and return one de-duplicated report using the required output contract with the smallest durable fix for each finding.
Pass supplied canonical diffs, snapshots, specs, or source artifacts to scouts instead of making them rediscover the same material.
Scouts return candidate evidence. The reviewer closes candidates before severity is assigned.
Trace every boundary used by the claim. For result/state findings, prefer:
semantic source
→ producer
→ validation/normalization
→ runtime/durable state
→ structured/public projection
→ model consumer
→ human/API consumer
→ docs/testsNot every step applies to every finding.
Find where the disputed fact originates and how it changes.
Do not infer semantic equivalence from similar field names. Trace producers and scope first.
Do not confuse representability with reachability.
A type, schema, fixture, or doc proves a value can be described. A behavioral finding requires a production path that can actually produce the material state/value.
If the harmful state cannot occur on the claimed path, dismiss or narrow the candidate.
Establish what the actual consumer receives.
For model-visible claims, determine whether the model gets content, details, both, or another transformation.
For human claims, distinguish compact TUI, expanded TUI, plain/RPC/JSON, and logs/files.
Never assume renderer-visible metadata is model-visible.
If a material conclusion depends on upstream behavior, resolve it for the repository's supported version range.
Prefer:
supported-version primary source/API/type contract
→ supported-version official docs
→ installed dependency source
→ targeted runtime smoke only if still unresolvedDo not substitute latest behavior for the supported range. Do not require a smoke test when source plus local integration already establishes the behavior.
When claiming a test gap or proposing a regression:
Would this test fail for the old bug and pass for the corrected behavior?
For lifecycle/recovery bugs, pair the harmful case with its nearest legitimate opposite when that distinction matters, such as a stale working parent versus a parent correctly waiting on unresolved child work.
Do not count assertion volume as coverage.
Every material candidate becomes exactly one of:
Unverified risk: evidence genuinely cannot be established with available read-only capabilities.An Unverified risk must state known evidence, missing evidence, version/runtime scope, why it matters, and one exact resolver.
Do not use it for an answerable question that was not investigated.
Own:
Can this state/value actually happen, where is it produced, and what runtime contract governs it?
Prove this liveness invariant for unresolved directly-owned assignments:
Every unresolved directly-owned assignment must either remain capable of making progress without its owner, or have a reliable reconciliation path that brings the exact owner back when action is required.
Trace:
schema/input
→ validation
→ effective configuration
→ execution
→ runtime/durable state
→ public result
→ next legal actionCheck:
working, blocked, settling, unknown, steerability, staleness, pending ask/result, child gating, cleanup convergence;Return exact production paths, reachability evidence, and candidate mismatches. Do not decide architecture from local evidence alone.
Own:
Who owns this rule, and is it truthful for the effective execution context?
Map:
system/base prompt
tool description
controller scope
shared agent prompt
role body
body @file
skills
dynamic success/error guidance
human docsFor each normative rule, find its intended single owner.
Flag:
DUPLICATE_AUTHORITY;CONTRADICTION;AUTHORITY_LEAK.Compare:
definition
→ override composition
→ effective tools/skills/extensions/context
→ launch args
→ actual role/depth
→ model instructions
→ presentationFind:
GHOST_CAPABILITY;HIDDEN_CAPABILITY;Return exact instruction text, owner, effective runtime evidence, and candidate conflicts.
Own:
Where does runtime truth go, what does each consumer actually see, and do docs/tests describe that contract?
Inspect list, assignment/steer/reply/close acknowledgements, completion delivery, errors, and truncation.
Ask:
Using only what the model actually receives, can it identify the source, understand the state, and choose the next legal action?
Flag missing correlation, hidden material details, ambiguous terminology, duplicated IDs, static policy repeated on every result, or missing dynamic next-action evidence.
For opacity candidates, trace projection semantics, not just field names.
Compare status widget, definitions view, completion renderer, warnings, compact/expanded views, and any plain/API surface.
Find hidden failures, duplicated data, display identity reused as machine identity, or UI claims stronger than runtime evidence.
Find shipped-but-undocumented behavior, documented-but-unshipped behavior, duplicate canonical owners, stale terminology, rejected examples, and implementation details presented as public contracts.
Find public contracts without discriminating regressions, tests that pass for correct and broken behavior, mocks that cannot detect claimed integration failures, missing sibling invariants, and stale fixtures.
Check package files, discovery, README links, AGENTS/maintainer guidance, validation scripts, dead compatibility/configuration, and removed concepts that still ship or remain referenced.
Return projection chains, consumer visibility, docs/tests evidence, and candidate mismatches.
Research is conditional. Once triggered, verification is required when capability exists.
Trigger researcher when:
a candidate likely to affect a P0-P2 finding, verdict, or remediation
depends on external API/runtime behaviorResearch input should contain only:
exact disputed assumption
supported version range
preferred primary source/repository
required direct answerRequire primary/official evidence, exact version relevance, and only material findings.
If web capability is unavailable:
Unverified risk.Do not add dependencies or require optional web tooling to run the audit.
Cover each applicable chain.
schema ↔ description ↔ validation ↔ errors ↔ docs ↔ testsdefinition ↔ override ↔ effective config ↔ launch ↔ role/depth ↔ tools/prompts ↔ presentationcontroller ↔ shared prompt ↔ role body ↔ skills ↔ dynamic resultslabel ↔ definition ↔ session ↔ request ↔ owner ↔ Herdr identity ↔ result/error/UIruntime evidence ↔ public state ↔ steerability ↔ eligibility ↔ displayed state ↔ next actioncompletion ↔ durable result ↔ result file ↔ owner message ↔ model content ↔ human rendering ↔ cleanupsyntax ↔ parsing ↔ merge ↔ validation ↔ effective metadata ↔ runtime ↔ persistence/UI ↔ docsfailure ↔ retained evidence ↔ autonomous progress/attention owner ↔ wake/delivery ↔ recurrence/termination ↔ structured error ↔ model/human guidance ↔ retry boundaryrepository ↔ package manifest ↔ installed files ↔ discovery ↔ maintainer guidanceCheck where applicable:
root | direct agent/parent | nested child/leaf | unmanaged sessionfresh | exact-session continuation | forkmodel content | structured details | compact TUI | expanded TUI | plain/RPC/JSON | logs/filessuccess | blocked | failure | rollback failure | close | cleanup pending | overflow | restart recoverybundled | partial override | standalone global | empty fields | false | [] | invalidUse consistently:
CONTRADICTION: authoritative surfaces prescribe incompatible behavior.GAP: required knowledge/behavior has no appropriate owner or result.GHOST_CAPABILITY: instructions/metadata claim unavailable capability.HIDDEN_CAPABILITY: required capability exists without enough safe guidance.DUPLICATE_AUTHORITY: one normative rule has multiple authoritative owners.AUTHORITY_LEAK: policy is owned by a layer that should not control it.CONTEXT_MISMATCH: rule is correct in one context and wrong in another.IDENTITY_AMBIGUITY: identity loses exact or single semantic meaning.STATE_AMBIGUITY: displayed/instructed state does not map cleanly to legal actions.RESULT_OPACITY: receiver lacks material source, state, correlation, outcome, or next-action evidence.FAIL_OPEN: missing/ambiguous evidence causes unsafe continuation.DRIFT: code, tests, docs, metadata, examples, or prompts describe different generations.TEST_BLIND_SPOT: material public contract lacks a discriminating regression.TOKEN_WASTE: repeated model context adds no decision value.DEAD_COMPLEXITY: compatibility/abstraction/state/configuration has no justified current use.UX_AMBIGUITY: human presentation obscures correct system behavior.Create another label only when none fits.
Do not inflate severity because a finding is interesting.
A material cross-surface finding needs:
A: semantic behavior/claim + exact source
B: conflicting/missing behavior/claim + exact source
Connection: why A and B are the same contract crossing a boundary
Reachability: production path when behavior is at issue
Consequence: what can actually go wrong
Minimal correction: narrowest root ownerA scout's conclusion is evidence, not authority.
The lead reviewer independently verifies every P0/P1, every P2 affecting architecture/verdict/external assumptions, and any disputed conclusion.
Do not report architectural preference as a defect.
Use these to find candidates. They do not replace closure.
details, hidden metadata, cleanup evidence, capability inference, state subconditions, correlation IDs.No findings.Optimize for useful evidence per agent, not agent count.
Exactly one:
PASS
PASS WITH FINDINGS
FAILPASS means no material P0-P2 findings after required surfaces were covered and material candidates were closed.
At most five bullets.
Order by severity, then confidence.
[P1][CONTEXT_MISMATCH] Short title
Evidence:
- path:line ...
- path:line ...
Why it matters:
...
Minimal durable fix:
...
Confidence: highDo not bury findings in prose.
Summarize meaningful ownership gaps/collisions across:
tool schema
tool description
controller scope
shared agent prompt
role body
skill
dynamic success guidance
dynamic error guidance
human docsFor:
input
capability
instruction
identity
state
completion
configuration
recovery
distributionreport:
status: verified | finding | not applicable | not verified
scope: what was actually tracedExample:
recovery | verified | startup rollback, retained cleanup evidence, retry markers
completion | finding | compact cleanup-warning projectionverified applies only to the stated scope. Do not claim whole-system PASS with unexplained not verified.
Give the shortest dependency-aware sequence.
Prefer:
fix root contract once
→ delete duplicate authority
→ add/update one discriminating regression
→ update canonical docsInclude only genuinely unresolved material claims after the closure workflow. State known evidence, missing evidence, version/runtime scope, consequence, and exact resolver.
Omit when empty.
Include only useful work not required to validate a material finding, such as a separate implementation task or non-material integration smoke.
Never put answerable material uncertainty here.
Omit when empty.
Normally return the lead reviewer's report instead of writing a second review.
Before returning, verify:
Unverified risk;If a check fails, return the report to the reviewer for reconciliation.
Otherwise stop.
Do not automatically fix findings.
If implementation is requested later:
implementer;A successful audit can answer without material guessing:
What can each agent actually do?
What is each agent told to do?
Who owns each normative rule?
Which identity is authoritative for each operation?
What does each public state permit next?
What changes by depth and generation?
What does the model see versus human/API surfaces?
Can each result be attributed to source/request?
Can each failure be acted on safely?
Can unresolved directly-owned work remain unnoticed forever?
Does effective configuration match prompts/presentation?
Are reported states and error fields reachable?
Do tests discriminate the important contracts?
Do docs/package contents describe what ships?
Is important authority duplicated or missing?
Is unjustified complexity present?If a material answer still requires guessing and the evidence was available, the audit is incomplete.
© boadij, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/agentic-system-audit of boadij/pi-herdsman.
Open the folder on GitHubat commit 3603d9f
Agentic System Audit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Agentic System Audit this skillboadij/pi-herdsman | 131 | — | ~5.8k | Automated safety check: Pass | Apache-2.0 | |
| Claude Code Agent Developmentanthropics/claude-plugins-official | 38k | 8 repos | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Subagent Driven DevelopmentAsvarox/allkaraoke | 261 | 38 repos | ~1.2k | Automated safety check: Pass | None | |
| Dispatching Parallel Agentsultralisp/ultralisp | 258 | 41 repos | ~1.5k | Automated safety check: Pass | None | |
| Paseo Advisor Second Opiniongetpaseo/paseo | 20k | 1 repos | ~756 | Automated safety check: Pass | Custom licence | |
| Task Observerrebelytics/one-skill-to-rule-them-all | 3.2k | 1 repos | ~12k | Automated safety check: Pass | CC-BY-4.0 |
anthropics/claude-plugins-official
Explains how to write agents for Claude Code plugins: the markdown file with YAML frontmatter, trigger descriptions, model and color settings, and system prompt design.
Asvarox/allkaraoke
A skill your agent uses when executing implementation plans with independent tasks in the current session
ultralisp/ultralisp
A skill your agent uses when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
getpaseo/paseo
Launches one separate agent through Paseo to give a second opinion on the current task, with a self-contained briefing and no permission to edit files.
rebelytics/one-skill-to-rule-them-all
Monitors task execution for skill improvement opportunities.
openobserve/openobserve
Splits a change into planner, coder and independent reviewer roles: you confirm a spec, a subagent implements it, and a separate reviewer checks each round's local WIP commit.
boadij/pi-herdsman
Write and review tests that protect meaningful Herdsman behavior without creating redundant, brittle, or low-value coverage.
boadij/pi-herdsman
Manage Pi Herdsman Agent definitions and managed Lead configuration.
boadij/pi-herdsman
Optional reinforcement and strategy for orchestrating managed agents.
Categories
Audit an agentic software system end to end for contradictions, gaps, inconsistent contracts, capability mismatches, instruction conflicts, ambiguous results, stale documentation, unsafe lifecycle…. Agentic System Audit is an agent skill from boadij/pi-herdsman. Audit an agentic software system end to end for contradictions, gaps, inconsistent contracts, capability mismatches, instruction conflicts, ambiguous results, stale documentation, unsafe lifecycle behavior, redundant guidance, missing enforcement, test blind spots, and architectural drift.
Agentic System Audit fits situations like: reviewing the overall health and coherence of an agent/tool system; especially systems with prompts; lifecycle state; dynamic results.
Run `npx skills add boadij/pi-herdsman --skill agentic-system-audit -a claude-code`. Or copy the skill folder (.agents/skills/agentic-system-audit in boadij/pi-herdsman) into .claude/skills/agentic-system-audit in your project. Claude Code loads it when a task matches its description.
Run `npx skills add boadij/pi-herdsman --skill agentic-system-audit -a codex`. Or copy the skill folder (.agents/skills/agentic-system-audit in boadij/pi-herdsman) into .agents/skills/agentic-system-audit in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add boadij/pi-herdsman --skill agentic-system-audit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agentic-system-audit, .gemini/skills/agentic-system-audit, .github/skills/agentic-system-audit and .opencode/skills/agentic-system-audit in your project.
SKILL.md names no scripts, command-line tools or credentials: Agentic System Audit is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Agentic System Audit is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 5.8k tokens (SKILL.md is roughly 23k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Agentic System Audit: Claude Code Agent Development (anthropics/claude-plugins-official, 38k stars), Subagent Driven Development (Asvarox/allkaraoke, 261 stars), Dispatching Parallel Agents (ultralisp/ultralisp, 258 stars) and Paseo Advisor Second Opinion (getpaseo/paseo, 20k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
boadij (a GitHub user) maintains it in boadij/pi-herdsman, which has 131 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 7, 2026.
Source: boadij/pi-herdsman on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.