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 getaero-io/gtm-eng-skills --skill warm-intro-scoringgit clone --depth 1 https://github.com/getaero-io/gtm-eng-skillsWrote 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/getaero-io/gtm-eng-skills/warm-intro-scoring)<a href="https://agentmods.dev/skills/getaero-io/gtm-eng-skills/warm-intro-scoring"><img src="https://agentmods.dev/badge/skills/getaero-io/gtm-eng-skills/warm-intro-scoring/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/getaero-io/gtm-eng-skills/warm-intro-scoring"><img src="https://agentmods.dev/badge/skills/getaero-io/gtm-eng-skills/warm-intro-scoring.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 | $0.00000 | $0.00073 |
| Opus 5.5 | $0.00000 | $0.00029 |
| Sonnet 5.5 | $0.00000 | $0.00015 |
| Haiku 4.5 | $0.00000 | $0.00007 |
Grade A, and why
warm-intro-scoring 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 22d 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
What ships with it
60 files 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.
- .gitignore 121 B
- assets/company-research.play.ts 1021 B runs code
- assets/customer-db.sql 2.7 KB
- assets/evaluation-example.json 4.6 KB
- assets/example.json 6.9 KB
- assets/portfolio-focus.weights.json 32 B
- assets/review.html 7.4 KB
- assets/tuning-example.json 1.2 KB
- assets/tuning.html 30 KB
- check_all.py 1.4 KB runs code
- GUIDE.md 4.7 KB
- LICENSE 1.1 KB
- package-manifest.json 9.8 KB
- plays/check_all.py 1.6 KB runs code
- plays/check_parity.py 6.0 KB runs code
- plays/check-report.py 1.8 KB runs code
- plays/collect.play.ts 4.0 KB runs code
- plays/collection.ts 1.9 KB runs code
- plays/core.ts 44 KB runs code
- plays/evaluation-contract.md 3.4 KB
- plays/evaluation.ts 14 KB runs code
- plays/features.play.ts 4.7 KB runs code
- plays/features.ts 23 KB runs code
- plays/generatedtemplate.ts 38 KB runs code
- plays/guardrails.ts 948 B runs code
- plays/legacy.ts 9.7 KB runs code
- plays/merge-payloads.py 8.6 KB runs code
- plays/parity-driver.ts 995 B runs code
- plays/parity-evaluation.py 8.5 KB runs code
- plays/parity-reports.py 2.3 KB runs code
- plays/prepare-inputs.py 6.5 KB runs code
- plays/quality.ts 3.8 KB runs code
- plays/read-sources.play.ts 3.4 KB runs code
- plays/README.md 18 KB
- plays/report-cli.ts 590 B runs code
- plays/report.play.ts 2.9 KB runs code
- plays/report.ts 3.1 KB runs code
- plays/reports.ts 5.7 KB runs code
- plays/research.play.ts 1.6 KB runs code
- plays/review-uncertainty.play.ts 5.5 KB runs code
- plays/score.play.ts 2.3 KB runs code
- plays/snapshots.play.ts 4.2 KB runs code
- plays/strict-json.ts 1.8 KB runs code
- plays/sync-template.py 849 B runs code
- plays/uncertainty.ts 4.9 KB runs code
- plays/validation.play.ts 3.6 KB runs code
- README.md 8.0 KB
- references/adversarial-review.md 7.0 KB
- references/batch-collection.md 5.1 KB
- references/company-network.md 5.8 KB
- references/competitive-review.md 8.8 KB
- references/evaluation.md 8.5 KB
- references/evaluator-validation.md 3.4 KB
- references/evaluator.md 7.9 KB
- references/external-data.md 4.0 KB
- references/factor-test-matrix.md 4.6 KB
- references/factors.md 6.1 KB
- references/intro-drafts.md 1.6 KB
- references/pipeline.md 7.6 KB
- references/readable-output.md 5.4 KB
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.
- 22d ago Changed · -81 lines · -34 tokens per session 9712978d3664
- 23d ago First seen · 87 lines · 34 tokens per session scan A e923fc1c45bf
warm-intro-scoring is a skill published in the GitHub repository getaero-io/gtm-eng-skills (68 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 73 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 2026-09-24.
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