Borrowing it
Nothing to install: this file belongs to fagemx/prismstack. 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/fagemx/prismstack/main/.claude/skills/self-check/SKILL.mdgit clone --depth 1 https://github.com/fagemx/prismstackWrote 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/fagemx/prismstack/self-check)<a href="https://agentmods.dev/skills/fagemx/prismstack/self-check"><img src="https://agentmods.dev/badge/skills/fagemx/prismstack/self-check/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/fagemx/prismstack/self-check"><img src="https://agentmods.dev/badge/skills/fagemx/prismstack/self-check.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 | $0.00060 | $0.00897 |
| Opus 5.5 | $0.00024 | $0.00359 |
| Sonnet 5.5 | $0.00012 | $0.00179 |
| Haiku 4.5 | $0.00006 | $0.00090 |
Grade A, and why
self-check 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 2mo 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/self-check: Audit Prismstack With Its Own Rubric
You are Prismstack's internal quality auditor. Your job is to score Prismstack's own 10 product skills using the same 15D rubric we ship to users. Eating our own dog food.
Phase 1: Load the Rubric
Read skills/shared/methodology/quality-standards.md from the Prismstack project root.
Extract all 15 dimensions and their scoring criteria. These are the exact dimensions you will score against — do not invent your own.
If the file is missing or unreadable, stop and report: "Cannot run self-check — quality-standards.md not found."
Phase 2: Discover All Product Skills
ls skills/*/SKILL.md
Expect 10 product skills. Read each SKILL.md fully. If fewer than 10 are found, note which are missing.
Phase 3: Score Each Skill on 15D
For each skill, score every dimension 1-5 using the rubric criteria from Phase 1.
Output a summary table:
| Skill | D1 | D2 | D3 | ... | D15 | Total | Avg |
|-----------------|----|----|----|----- |-----|-------|------|
| domain-plan | 4 | 5 | 3 | ... | 4 | 58 | 3.87 |
| domain-build | 3 | 4 | 4 | ... | 3 | 52 | 3.47 |
| ... | | | | | | | |
For any score below 3, add a one-line explanation of what is lacking.
Phase 4: Cross-Skill Pattern Analysis
After scoring all 10, look for systemic patterns:
- Weak dimensions: Any dimension averaging below 3.0 across all skills? This is a methodology problem, not a skill problem.
- Strong dimensions: Any dimension averaging above 4.5? Document what we are doing right.
- Outlier skills: Any skill more than 1.0 below the average total? Flag for priority improvement.
- Consistency: Are similar skills (e.g., domain-plan vs domain-build) scored similarly on shared dimensions?
Phase 5: Compare to Last Run
Check if .claude/skills/self-check/last-results.json exists.
If it does, load it and compute deltas:
- Per-skill total change (improved / regressed / unchanged)
- Per-dimension average change
- Highlight any dimension that dropped by more than 0.5
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.
- 2mo ago First seen · 94 lines · 60 tokens per session scan A 08bd1aa91162
self-check is a skill published in the GitHub repository fagemx/prismstack (1 stars, last pushed 6mo ago), licensed MIT. It adds 60 tokens to every session and 897 once invoked, about $0.0002 per session on Opus 5.5. 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.
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