Borrowing it
Nothing to install: this file belongs to ZoneMinder/zmNinjaNg. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ZoneMinder/zmNinjaNg/main/.claude/skills/fable-review/SKILL.mdgit clone --depth 1 https://github.com/ZoneMinder/zmNinjaNgWrote 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/zoneminder/zmninjang/fable-review)<a href="https://agentmods.dev/skills/zoneminder/zmninjang/fable-review"><img src="https://agentmods.dev/badge/skills/zoneminder/zmninjang/fable-review/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/zoneminder/zmninjang/fable-review"><img src="https://agentmods.dev/badge/skills/zoneminder/zmninjang/fable-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 78 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00077 | $0.04010 |
| Opus 5 | $0.00039 | $0.02005 |
| Sonnet 5 | $0.00015 | $0.00802 |
| Haiku 4.5 | $0.00008 | $0.00401 |
Grade A, and why
fable-review 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 10d 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 — 265 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fable Codebase Review
Overview
A scored, multi-pillar codebase review whose output is a report another agent (Opus) executes without re-deriving anything. The pillars and the report shape come from the first run of this review (issue #217, PR #218, overall 7.5 to 8.1); the rules below are what that run and its two follow-up reviews proved necessary.
Core principle: every finding was confirmed by reading the file it cites. A grep hit is a lead, not a finding, and a pillar score with no evidence under it is an opinion that does not get a number.
Second principle: the report is executed by an agent that cannot see this session. Anything a finding leaves implicit - the fix, the verification, the risk, the reason a nearby thing must not change - is work the executor will get wrong.
Preconditions (check both before anything else)
Clean context
The review must start from a clean context. A session that has already done implementation work carries the assumptions it made while working, and it will grade its own output: gates it stopped checking read as green, code it wrote reads as idiomatic, and drift it introduced becomes invisible. Re-running these checks from a fresh context is the point of the review.
If this session already holds prior work - edits, debugging, a long conversation, or anything beyond the invocation itself - stop and say:
This review needs a clean context. Start a fresh session (
/clear, orclaude -p "/fable-review"from a new shell) on Fable, then run/fable-reviewthere.
Pillar agents inherit this: each gets a fresh context and a written brief. Never paste session history into a dispatch.
Model
This review runs on Fable only. Fable's judgment across a whole
repository is the deliverable; the orchestrator's model bounds everything
under it (see Orchestration in agents/generic/claude-workflows.md).
- Your own system prompt names the model you are running as.
- If that name is not Fable (model id
claude-fable-5), stop immediately. Read nothing, dispatch nothing, write nothing. - Say exactly this and end the turn:
What ships with it
1 file 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.
- 10d ago First seen · 265 lines · 77 tokens per session scan A 85c5fab338b8
fable-review is a skill published in the GitHub repository ZoneMinder/zmNinjaNg (108 stars, last pushed today), licensed Apache-2.0. It adds 77 tokens to every session and 4,010 once invoked, about $0.0004 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 2026-08-30.
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