Borrowing it
Nothing to install: this file belongs to lowtidebuild/public-equity-research. 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/lowtidebuild/public-equity-research/main/.claude/skills/quality-checker/SKILL.mdgit clone --depth 1 https://github.com/lowtidebuild/public-equity-researchWrote 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/lowtidebuild/public-equity-research/quality-checker)<a href="https://agentmods.dev/skills/lowtidebuild/public-equity-research/quality-checker"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/quality-checker/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/lowtidebuild/public-equity-research/quality-checker"><img src="https://agentmods.dev/badge/skills/lowtidebuild/public-equity-research/quality-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Anti-Refusal · line 108 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00000 | $0.03107 |
| Opus 5 | $0.00000 | $0.01554 |
| Sonnet 5 | $0.00000 | $0.00621 |
| Haiku 4.5 | $0.00000 | $0.00311 |
Grade A, and why
quality-checker 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 11d 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 — 341 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quality Checker — SKILL.md
Role: Step 9 — Perform output-facing quality checks and rebuild the deterministic run-local quality report before delivery to user. Auto-patch minor issues; flag persistent failures inline.
Triggered by: CLAUDE.md after Step 8 (output generation), before final delivery
Reads: Generated output file (or inline response), run-local validated-data.json, run-local evidence-pack.json, optional run-local context-budget.json, run-local analysis-result.json
Writes: Patches to the output file; run-local quality-report.json
References: None (quality standards defined in this file)
Instructions
Pre-Check Setup
Load:
- The generated output (HTML file, Markdown file, or inline text)
- run-local
validated-data.json(for grade reference) - run-local
evidence-pack.json(for compact fact/source references and raw access policy) - run-local
context-budget.jsonif present (for deterministic context budget and routing policy confirmation) - run-local
analysis-result.json(for scenario probabilities and R/R Score) - Existing run-local
quality-report.jsonif present (merge output-facing checks with contract/semantic checks)
After the output-facing checks, rebuild the canonical run-local quality report:
python .claude/skills/quality-checker/scripts/quality-report-builder.py --run-dir output/runs/{run_id}
Mode A Lightweight Check
Mode A uses a lightweight quality check. It still checks disclaimer, as-of date, the three KPI tiles, and Grade D blank-over-wrong behavior, but it does not run the full 80% source-tag coverage rule across every number in the briefing. No Critic Agent is dispatched for Mode A.
IF output_mode = "A":
Run Items 1, 2, 3, 5
Run Item 4 as the Mode A KPI-only attribution rule:
- three KPI tiles must be present
- each KPI value must have a source tag or confidence grade
- analysis_date must be visible as the as-of date
Skip Critic dispatch
Write quality-report.json with deterministic rendered_output result when report_path is available
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.
- 11d ago First seen · 341 lines · 0 tokens per session scan A 21bed867a771
quality-checker is a skill published in the GitHub repository lowtidebuild/public-equity-research (46 stars, last pushed 1mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 3,107 tokens. 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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