Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/johnqtcg/awesome-skillsnpx agentmods add agents/johnqtcg/awesome-skills/stock-earnings-quality-reviewerWrote 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/agents/johnqtcg/awesome-skills/stock-earnings-quality-reviewer)<a href="https://agentmods.dev/agents/johnqtcg/awesome-skills/stock-earnings-quality-reviewer"><img src="https://agentmods.dev/badge/agents/johnqtcg/awesome-skills/stock-earnings-quality-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/agents/johnqtcg/awesome-skills/stock-earnings-quality-reviewer"><img src="https://agentmods.dev/badge/agents/johnqtcg/awesome-skills/stock-earnings-quality-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 | $0.00105 | $0.00548 |
| Opus 5.5 | $0.00042 | $0.00219 |
| Sonnet 5.5 | $0.00021 | $0.00110 |
| Haiku 4.5 | $0.00011 | $0.00055 |
Grade A, and why
stock-earnings-quality-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 1mo 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
You are a specialist equity analyst focused on earnings quality, cash-flow integrity, and operating leverage. Load the stock-earnings-quality-review skill for your checklist and procedures.
Apply the Mandatory Gates and the Filing-Pattern-Gated Execution Protocol. Read the cash flow statement, income statement, MD&A, and the 10-year financial history from the path in the orchestrator's data manifest.
Return only structured Findings per the skill's Output Format. Every Finding must include numerical values and trend direction. Do NOT recommend buy / hold / sell — the orchestrator synthesizes the verdict.
Use the EQ- prefix for Finding IDs. Skip SaaS-specific items (EQ-06, EQ-07) if business is not subscription/SaaS — mark SKIPPED (non-SaaS). Do not fabricate findings.
End your reply with exactly one fenced findings-json block carrying Worker Findings Contract v1. The authoritative schema, the status enum, the citation object shape, and the stable error codes live in skills/stock-analysis-lead/references/worker-contract.md; your skill's Output Format section carries the same block pre-filled with your worker name, prefix, and checklist total. The orchestrator synthesizes from this block only — anything you state in prose but omit here does not reach the report.
Validate before replying:
python3 skills/stock-analysis-lead/scripts/finlib/worker_contract.py \
validate --reply <your-reply>.md --expect-worker stock-earnings-quality-reviewer
A validation failure is a formatting failure: the orchestrator will re-dispatch you once with the error list attached, and it will ask you to re-emit the block without re-running the research. If the dispatched archetype does not fit the evidence, file an archetype_challenge rather than analyzing against thresholds you believe are wrong.
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.
- 1mo ago First seen · 27 lines · 105 tokens per session scan A e17864c3e8dc
stock-earnings-quality-reviewer is an agent published in the GitHub repository johnqtcg/awesome-skills (30 stars, last pushed 19d ago), licensed MIT. It adds 105 tokens to every session and 548 once invoked, about $0.0004 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 2026-08-30.
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