agentsclimarketplace

Scoped audit

Skill emaraschio/cursor-commands/.cursor/skill-contracts/scoped-audit

Production-grade Cursor slash commands with paired skill contracts, behavioral evals, and ship-gate CI. Install as a user plugin.

Install
npx -y skills add emaraschio/cursor-commands --skill scoped-audit

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 9 stars9 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Scoped, plan-first workflow for large "check-N-things" tasks (audits, inventories, catalogs, large migrations, cross-checks). Decomposes the surface, fans out capped parallel subagents, verifies findings before reporting, and gates any change behind explicit approval. Use for "audit X for Y", "find all", "catalog every", "inventory", "migrate across", or any repeatable workflow that has quietly become "check 400 things".

SKILL.md

5.9 KB, ~1.2k tokens by cl100k_base, as published. Nobody here has run it

Scoped audit

Role

You orchestrate a large, repetitive task as a scoped workflow. The goal is a trustworthy catalog of verified findings (and, only when asked and approved, a set of changes derived from them). Big surfaces are where agents hallucinate and burn tokens; this contract exists to prevent both.

When to use

Use this skill when the task is "do one thing" repeated across a large surface: audit every flag, catalog every call site, inventory every config, cross-check every doc, or migrate a pattern repo-wide. For a single requirement or a single-file change, use requirement-to-implementation instead.

Workflow

Run phases in order. Do not make changes until Phase 3 (approval) passes. Do not report a finding until Phase 6 (verification) confirms it.

Phase 0: Scope

  1. Restate the target surface and the question being asked in one sentence.
  2. Bound the surface: which directories, repos, file globs, or datasets are in and out of scope.
  3. Define what a single "finding" is and the exact pass/fail condition for it.
  4. If the surface or success condition is ambiguous, ask one focused question before proceeding (use AskQuestion when available).

Phase 1: Plan (show before running)

Present the plan to the user and wait. The plan must show, explicitly:

  1. Stages: the ordered steps of the workflow.
  2. Subagent responsibilities: what each parallel subagent will inspect, and how the surface is partitioned across them.
  3. Verification method: how each finding will be confirmed against the source before it is reported.
  4. Files and commands to touch: read paths for the audit; for any proposed change, the write paths and commands.
  5. Smallest safe first pass: the scoped sample you will run before fanning out across the whole surface.

Phase 2: Scoped sample (first pass)

  1. Run the workflow against the scoped sample only, never the full surface first.
  2. Confirm the finding shape, the partition strategy, and the verification method actually work.
  3. Report sample results and the projected cost/scale of the full run. Surface the token-burn risk: parallel fan-out across a large surface compounds quickly.

Phase 3: Approval gate (hard stop)

  1. Do not expand beyond the scoped sample, and do not make any change, until the user gives approval for the full plan.
  2. If the scoped sample revealed the plan was wrong, return to Phase 1 and re-plan rather than pushing forward.

Phase 4: Parallel fan-out (capped)

  1. Partition the approved surface into independent slices.
  2. Launch parallel subagents (Cursor explore for read-only discovery, generalPurpose for analysis), one slice each. Cap concurrency at ≤ 6 to bound token burn and keep results reviewable. Batch additional slices in waves.
  3. Each subagent returns structured findings for its slice only; it does not make changes.

Phase 5: Aggregate

  1. Merge subagent results into a single catalog, de-duplicated by a stable key.
  2. Normalize the finding records so every row has the same fields.

Phase 6: Verify (before reporting)

  1. Verify findings before reporting them: re-check each candidate finding against the actual source (re-read the file, re-run the query) rather than trusting a subagent's summary.
  2. Drop or flag any finding that cannot be confirmed. Never report an unverified finding as fact.
  3. Note coverage gaps: slices that failed, timed out, or were skipped.

Phase 7: Report

  1. Present the verified catalog (table or list) plus a short summary: total found, verified, unverified, and coverage gaps.
  2. If the user asked for changes (e.g. a migration), present them as a separate proposed change set with the affected files and commands, and return to an approval gate before editing anything.

Output template

# Scoped audit: <surface> (<question>)

## Scope
- In: <paths/globs/datasets>  | Out: <excluded>
- Finding = <definition>; condition = <pass/fail rule>

## Coverage
| Slices | Completed | Failed/skipped |

## Findings (verified)
| # | Location | Value / detail | Verified | Notes |

## Unverified / needs review
| # | Location | Why unconfirmed |

## Proposed changes (only if requested, requires approval)
| File | Change | Command |

Safety

  • Make no changes (no edits, migrations, or destructive commands) until the plan is approved.
  • Never log or echo secrets, tokens, credentials, PII, or PHI encountered while scanning the surface; redact them in findings.
  • Respect the concurrency cap; do not spawn unbounded subagents.
  • Prefer reporting a coverage gap over fabricating a complete-looking result.

Distinction from other commands

  • requirement-to-implementation: one requirement → build it. This skill is many repeated checks across a large surface, audit-first.
  • security-audit, seo-audit, accessibility-audit: single-domain audits with domain rubrics. This skill is domain-agnostic orchestration. Use it to drive a large cataloging pass, and lean on the domain skill for what counts as a finding when relevant.
  • This skill catalogs and proposes; it does not edit until a separate approval gate, even when the surface is read with write tools available.

Guardrails

  • Run a scoped sample first; never sweep the full surface before the approach is validated.
  • Verify findings before reporting them; never report an unverified finding as fact.
  • Make no changes until the plan has explicit approval; respect the subagent concurrency cap and redact secrets in findings.

What ships with it: 3 files

3.8 KB alongside SKILL.md

eval/

Keep looking

Skills are one crate of 326,970. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.