audit
Skill0 starsChanged 12 days agoApache-2.0View on GitHub
Audit the diff against the plan in fresh context.
194 other projects use a version of this.
Adopted by
Most recently taken up by
- Laucked-Security/claude-oswetheir own version, first seen Nov 8, 2026
- sanmidable/skillstheir own version, first seen Nov 8, 2026
- alegauss/claude-traytheir own version, first seen Nov 8, 2026
- ansvisor/ansvisortheir own version, first seen Nov 8, 2026
- ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tooltheir own version, first seen Nov 8, 2026
- MammadovEshgin/clean-code-skilltheir own version, first seen Nov 8, 2026
Used with
Projects with it also use delight, teach-impeccable and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
HK-hubSkilldelight
Add moments of joy, personality, and unexpected touches that make interfaces memorable and enjoyable to use. Elevates functional to delightful. Use when the user asks to add polish, personality, animations, micro-interactions, delight, or make an interface feel fun or memorable.
Also in 32 projects that use this
HK-hubSkillteach-impeccable
One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.
Also in 19 projects that use this
zwy123zwySkillnormalize
将用户随意输入的提示词规范化为结构清晰、便于大模型执行的标准化提示词。适用于需要整理、统一提示词格式时调用。
Also in 19 projects that use this
SkillPilotCHSkilllevel-up
Eine Automatisierung pro Woche finden, scopen, shippen. Output landet als proposed-Eintrag in cadence.md mit konkreten Implementations-Schritten.
Also in 12 projects that use this
ww-w-aiSkillpm-discovery
PM Agent Team - Automated product discovery, strategy, and PRD generation. Runs PM analysis workflow to produce comprehensive PRD before PDCA Plan phase.
Also in 3 projects that use this
- +7 more from HK-hub
Other versions194 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 194
- openai/plugins★ 7.8ksame name
- ccch1mneyyy/dsh-TUI★ 7.2ksame name
- macro-inc/macro★ 6ksame name
- yournextstore/yournextstore★ 5.5ksame name
- gadievron/raptor★ 4ksame name
- alchemy-run/alchemy★ 1.9ksame name
- alchemy-run/alchemy-effect★ 1.9ksame name
- mattmireles/gemma-tuner-multimodal★ 1.5ksame name
- jsmastery-pro/skills★ 1.4ksame name
- nateherkai/AIS-OS★ 1.4ksame name
184 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository24 other files it gives its agents.
- .claude/CLAUDE.mdCLAUDE.md
- closeSkill
- doctorSkill
- editorSkill
- execSkill
- knowledgeSkill
- openSkill
- package-mapSkill
- plan-reviewSkill
- planSkill
- preflightSkill
- prSkill
- pr-statusSkill
- pr-syncSkill
- quickfixSkill
- resetSkill
- resumeSkill
- review-prSkill
- sliceSkill
- syncSkill
- triageSkill
- upstream-rulesSkill
- validateSkill
- worktree-kitSkill
The file
We split this skill into the rules it gives an agent
1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 176 edited versions we read keep these.
0
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 65
Write it as returned. Opening the files to check a finding is reading the diff here after all.
“Common” is measured: kept by at least 6 in 10 of the 176 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Via pd-auditor, which sees the diff and the plan and nothing else — not the
implementer's reasoning, which is exactly what would make it agree.
Preconditions
pdkit state <issue> says validated. Auditing before validation means
auditing a diff nobody has run.
1. The facts
pdkit audit <n> --base mainState and route, the frozen requirement set, every task with its Owns and
satisfies, the state of every receipt, the changed files, and three findings
that need no judgment at all:
- files changed outside every task's ownership — the pre-write hook is silent when no task was ever started, so this is the only place such a change is certain to be seen;
- requirements with no task;
- tasks with no requirement;
- tasks no
pd-implementerran for, from theagent-doneentries the journal tied to each task. A task started before the journal recorded any subagent isnot recorded, which is not the same as none.
This command reports and never decides. It exits zero whatever it finds.
pd-auditor runs it, not this session. On a large issue the report lists
every task and every changed file, and that belongs in the context that reads
the diff.
2. The three questions
Dispatch pd-auditor with the issue number and the base, and nothing else.
It runs pdkit audit and reads git diff main...HEAD and the plan in its own
context. Do not read the diff here, not even to hand it over: the auditor's
context ends when it returns, and this session's is paid for again on every
turn until it ends. What comes back is the short form at the end of
${CLAUDE_PLUGIN_ROOT}/agents/pd-auditor.md, and that is all this session needs.
It does not get the implementer's account of the work — a summary of why the code is right is the most persuasive thing in the room and the least evidential.
- Which requirements have no code? (The map says which have no task. Whether the code under a task actually implements the requirement is the question.)
- Which code answers no requirement?
- What changed inside
Ownsthat the task never asked for?
3. The verdict
audit.md under the issue is the auditor's answer as it came back: findings
first, each with a file and a line, then what it could not judge by reading.
Write it as returned. Opening the files to check a finding is reading the diff
here after all; a finding you doubt goes back to pd-auditor as a question.
Two disciplines, both from the same failure mode. An auditor told to find problems will find them in correct code, so: an empty findings section is a valid result, and style is not a finding. And where you are uncertain, say uncertain — fresh context catches drift from the plan, not blind spots shared with the model that wrote the code.
Then
pdkit state <n> --to audited when the findings are addressed or accepted.
Unaddressed findings are not a reason to skip the transition quietly — they go
in audit.md and the state stays where it is.
When the phase runs long
budget.turns.audit is low on purpose. The facts come from pdkit audit, the
reading from pd-auditor, and an audit that runs long is usually this session
reading the diff itself — the auditor's job, in its own context. The number is
a guide rather than a count anyone keeps. Past it, write what has been found to
audit.md and ask for a restart.
Next
/pd:slice <issue> — the change set becomes a verified graph of atomic pull
requests, even when the graph turns out to have one node.
In a new session. Slicing works from the finished diff and from
slice suggest, and what it needs of the audit is in audit.md. The
conversation that produced the findings has no further vote, and carrying it
forward means paying for it on every turn of the slicing. pdkit next <issue>
prints the line.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

