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 Eliyce/paqad-ai --skill content-reviewergit clone --depth 1 https://github.com/Eliyce/paqad-aiWrote 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/eliyce/paqad-ai/content-reviewer)<a href="https://agentmods.dev/skills/eliyce/paqad-ai/content-reviewer"><img src="https://agentmods.dev/badge/skills/eliyce/paqad-ai/content-reviewer/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/eliyce/paqad-ai/content-reviewer"><img src="https://agentmods.dev/badge/skills/eliyce/paqad-ai/content-reviewer.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 | $0.00035 | $0.00323 |
| Opus 5 | $0.00017 | $0.00161 |
| Sonnet 5 | $0.00007 | $0.00065 |
| Haiku 4.5 | $0.00003 | $0.00032 |
Grade A, and why
content-reviewer 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 9d 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.
What it actually says
Content Reviewer
What It Does
Runs a structured review pass over a draft so feedback is concrete (line + heuristic + required action) instead of subjective.
Use This When
Use this when a draft is ready for review and the team wants consistent, traceable feedback rather than personal taste.
Inputs
- The draft markdown / copy.
- The project's writing-style file at
docs/instructions/rules/writing-style.mdwhen it exists. references/review-rubric.mdfor the review heuristics.
Procedure
- Run
scripts/scan-prose.sh <draft>to surface candidate issues (filler, hedge, passive, jargon, vague this, long lines, broken links). - For each hit, decide if it's an actual problem given the audience defined by the brief.
- Walk every heuristic in
references/review-rubric.md; never skip a category silently. - Format findings per
assets/output.template.md. - Validate with
scripts/lint-output.sh.
Output Contract
- Match
assets/output.template.md:## Blocking Issuesand## Improvement Opportunities. - Output must pass
scripts/lint-output.sh.
Resources
references/review-rubric.mdscripts/scan-prose.shscripts/lint-output.shassets/output.template.md
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 41 lines · 35 tokens per session scan A 53e36e41d8db
content-reviewer is a skill published in the GitHub repository Eliyce/paqad-ai (8 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 323 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 2026-09-03.
Other skills, from other repositories
pr-writing-review
Extract and analyze writing improvements from GitHub PR review comments. Use when asked to show review feedback, style changes, or editorial improvements from a GitHub pull request URL. Handles both explicit suggestions and plain text feedback. Produces structured output comparing original phrasing with reviewer…
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auto-go
A command that implements code from a SPEC, a document describing the required behavior and work.
auto-plan
A code-planning skill that examines a codebase and creates a detailed specification, implementation plan, and acceptance criteria. It can organize requirements using EARS, a structured way to describe how software should behave in different situations.
agent-pipeline
Multi-agent pipeline orchestration skill.
adaptive-quality
Per-task execution profile selection based on complexity in Balanced quality mode.