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 Glad-Labs/poindexter --skill quality-reportgit clone --depth 1 https://github.com/Glad-Labs/poindexterWrote 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/glad-labs/poindexter/quality-report)<a href="https://agentmods.dev/skills/glad-labs/poindexter/quality-report"><img src="https://agentmods.dev/badge/skills/glad-labs/poindexter/quality-report/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/glad-labs/poindexter/quality-report"><img src="https://agentmods.dev/badge/skills/glad-labs/poindexter/quality-report.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 | $0.00044 | $0.00424 |
| Opus 5 | $0.00022 | $0.00212 |
| Sonnet 5 | $0.00009 | $0.00085 |
| Haiku 4.5 | $0.00004 | $0.00042 |
Grade A, and why
quality-report 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.
What it actually says
Quality Report
Shows recent tasks that have cleared the multi-model QA pipeline, grouped by status. The pipeline ends in one of two terminal states (not "completed" — that status was removed in the 2026-04 refactor):
- awaiting_approval — passed QA, waiting on human review at
/pipeline - published — approved and pushed to the site via Vercel
Each task carries a quality_score populated by multi_model_qa.py after the
anti-hallucination QA rails finish. Six OSS rails run (all advisory): DeepEval ×3
(deepeval_brand_fabrication, deepeval_g_eval, deepeval_faithfulness),
guardrails ×2 (guardrails_brand, guardrails_competitor, native/dep-free since
#996), and Ragas ×1 (ragas_eval, averaging faithfulness + answer-relevancy +
context-precision).
Usage
scripts/run.sh # Both awaiting_approval + published, last 10 each
scripts/run.sh awaiting [limit] # Just the human-review queue
scripts/run.sh published [limit] # Just posts that went live
Parameters
mode(optional):awaiting|published|all(default)limit(optional): number of tasks per group. Defaults to 10.
Output
For each task: id, title, topic, quality_score, updated_at.
Score range is 0–100 from the multi-model QA aggregator. 80+ is typical for
approved posts; anything that got below the qa_final_score_threshold setting
(currently 80) never reaches these states — it gets rejected.
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 · 41 lines · 44 tokens per session scan A f2e2530dab66
quality-report is a skill published in the GitHub repository Glad-Labs/poindexter (5 stars, last pushed today), licensed Apache-2.0. It adds 44 tokens to every session and 424 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.
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