Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add joelbrilliant/agentic-delivery-skills --skill reviewer-fix-modegit clone --depth 1 https://github.com/joelbrilliant/agentic-delivery-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/joelbrilliant/agentic-delivery-skills/reviewer-fix-mode)<a href="https://agentmods.dev/skills/joelbrilliant/agentic-delivery-skills/reviewer-fix-mode"><img src="https://agentmods.dev/badge/skills/joelbrilliant/agentic-delivery-skills/reviewer-fix-mode/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/joelbrilliant/agentic-delivery-skills/reviewer-fix-mode"><img src="https://agentmods.dev/badge/skills/joelbrilliant/agentic-delivery-skills/reviewer-fix-mode.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.00552 |
| Opus 5 | $0.00024 | $0.00276 |
| Sonnet 5 | $0.00010 | $0.00110 |
| Haiku 4.5 | $0.00005 | $0.00055 |
Grade A, and why
reviewer-fix-mode scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reviewer Fix Mode
Overview
Use this skill when reviewers are allowed to fix issues they find.
Reviewer-fix mode is useful, but only if the review happens first and the fix scope is locked to documented findings.
When to Use
- A reviewer may patch issues after review.
- A review found clear defects and the owner authorises direct repair.
- A strict harness lets reviewers fix after documenting findings.
- You need to stop reviewer scope drift.
- Orchestrator must final-sign off reviewer fixes.
Non-negotiable Sequence
- Review first. Write findings before editing.
- Declare mode. Say reviewer-fix mode is starting.
- Fix only documented findings. No opportunistic cleanup.
- Verify fixes. Run targeted tests and relevant smoke checks.
- Report separately. Keep review findings and fix evidence distinct.
- Return to orchestrator. Reviewer does not self-merge by default.
Finding Format
### HIGH-1: [summary]
- Evidence: file.py:LN
- Regression analysis: if X changes, which test catches it?
- Fix scope: exactly what may change
Fix Report Format
## Reviewer-fix mode report
### Fixed findings
- HIGH-1: [what changed]
### Changed files
- path/file.py
### Verification
- command: result
- runtime/API/browser proof: result
### Out of scope
- [things noticed but not fixed]
### Remaining risk
- [none / listed]
Allowed Fixes
Allowed:
- direct bug fixes for documented findings;
- regression tests for documented findings;
- small refactors required to fix the finding;
- docs updates that explain changed behaviour.
Not allowed without orchestrator approval:
- new features;
- design/product changes;
- broad formatting;
- architecture rewrite;
- unrelated test cleanup;
- changing public contracts beyond the finding.
Orchestrator Final Check
The orchestrator checks:
- every fix maps to a documented finding;
- no unrelated files changed;
- tests prove the regression mode;
- production-shaped path is covered if relevant;
- reviewer did not silently become second builder.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 99 lines · 49 tokens per session scan A 028943f2533a
reviewer-fix-mode is a skill published in the GitHub repository joelbrilliant/agentic-delivery-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 49 tokens to every session and 552 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
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Linting and formatting for Megatron-LM. Covers running autoformat.sh, tools (ruff, black, isort, pylint, mypy), and code style rules.
package-evaluator
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code-refiner
Deep code simplification and refactoring preserving behavior across Python, Go, TypeScript, Rust. Targets complexity, anti-patterns, readability debt. Triggers on: "simplify this code", "refactor for clarity", "reduce complexity", "make this more readable", "tech debt cleanup", "too much nesting".
codebase-advisor
Senior codebase advisor that audits a repository, vets findings, and writes self-contained implementation plans for other agents to execute. Triggers on: "write improvement plans", "create an implementation backlog", "audit and plan fixes", "turn findings into plans", "agent-executable plans", "reconcile plans"…
pr-review
Diff-based PR review across code quality, test coverage, silent failures, type design, and comment quality with severity-ranked findings. Triggers on: "review my PR", "review this code", "check my changes", "audit this PR", "code review". NOT for pre-landing gate, use pre-landing-review.
devils-advocate
Challenges AI-generated plans, code, and designs via pre-mortem, inversion, and Socratic questioning to surface blind spots and failure modes. Triggers on: "challenge this", "devils advocate", "stress test this plan", "poke holes in this", "what am I missing".