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 int2t05/engineering-skills --skill researchgit clone --depth 1 https://github.com/int2t05/engineering-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/int2t05/engineering-skills/research)<a href="https://agentmods.dev/skills/int2t05/engineering-skills/research"><img src="https://agentmods.dev/badge/skills/int2t05/engineering-skills/research/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/int2t05/engineering-skills/research"><img src="https://agentmods.dev/badge/skills/int2t05/engineering-skills/research.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 | $0.00026 | $0.00518 |
| Opus 5.5 | $0.00010 | $0.00207 |
| Sonnet 5.5 | $0.00005 | $0.00104 |
| Haiku 4.5 | $0.00003 | $0.00052 |
Grade A, and why
research 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 15d 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 — 41 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research
When to use
- Investigate a question using verifiable sources and comparable criteria.
Not for: design-research for visuals; spec for requirements.
Steps
-
Agree the question, decision, coverage and output path; choose general, market or tech-selection mode.
-
Read primary documentation and relevant real repository files. Record source, commit and implementation evidence; report unavailable community sources.
-
Compare candidates on the same requirements. Separate facts, inference and uncertainty; failed searches do not prove absence.
-
Lead with usefulness, applicability and recommendation, then evidence and limits. Explain what additional evidence could change the decision.
Output: Suggested paths, subject to human audit: docs/research/YYYY-MM-DD-<slug>.md, docs/research/market.md or docs/research/competitor.md; prefer its existing owner.
Verify
- Claims trace to retrieved evidence; candidates share criteria and missing coverage is explicit.
References
- engineering-principles.md — shared decision boundaries, scope and verification.
- human-audit.md — document consent, readability and human review.
- product-principles.md — product discipline (the real competitor is the current workaround). Linked by market + tech-selection modes.
- references/report-spine.md — reader-first organization, evidence, diagram selection and human review.
- references/general-mode.md — question framing, primary sources and bounded synthesis.
- references/market-mode.md — problem, alternatives, sizing and distribution evidence with selection-bias limits.
- references/tech-selection-mode.md — actual constraints, implementation evidence and comparable selection criteria.
- references/web-tool-fallback.md — when a fetch tool is blocked or quota-exhausted: tiered fallback by quota dependency (GitHub → indexed docs → scrape → discovery), orthogonal to page-level retries.
- references/pressure-scenarios.md — behavioral scenarios for certainty, access gaps, popularity and report bloat.
What ships with it
9 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.
- agents/openai.yaml 127 B
- references/general-mode.md 1.8 KB
- references/market-frameworks.md 6.1 KB
- references/market-mode.md 2.0 KB
- references/pressure-scenarios.md 1.3 KB
- references/report-spine.md 2.1 KB
- references/selection-rubric.md 5.9 KB
- references/tech-selection-mode.md 2.2 KB
- references/web-tool-fallback.md 3.5 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.
- 15d ago Changed · -97 lines · +26 tokens per session bee42ca626bb
- 21d ago Changed · +1 lines c5ba3c37e767
- 2mo ago First seen · 137 lines · 0 tokens per session scan A 405563e2356c
research is a skill published in the GitHub repository int2t05/engineering-skills (3 stars, last pushed 15d ago), licensed MIT. It adds 26 tokens to every session and 518 once invoked, about $0.0001 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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pr-workflow
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