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 tony/skills --skill researchgit clone --depth 1 https://github.com/tony/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/tony/skills/research)<a href="https://agentmods.dev/skills/tony/skills/research"><img src="https://agentmods.dev/badge/skills/tony/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/tony/skills/research"><img src="https://agentmods.dev/badge/skills/tony/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 | $0.00024 | $0.01618 |
| Opus 5.5 | $0.00010 | $0.00647 |
| Sonnet 5.5 | $0.00005 | $0.00324 |
| Haiku 4.5 | $0.00002 | $0.00162 |
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 5d 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Business Research
Collect the data behind a business-value claim for an AI skill or agentic workflow (productivity, time saved, quality, capacity, delivery outcomes) into the interim run package the report skills render from.
Read these first; they bind every step:
../../references/interim-format.md: the run package layout, where runs live, and the value units (never money).../../references/provenance.md: the four tags and the anti-inflation rules.../../references/instruments.md: per-instrument probes, collection discipline, the pull-request query, and the targets to collect.
Load ../../references/measurement.md only for the counterfactual
ladder and the statistics discipline, which owns the n<5 range rule.
Intervals come from ../../scripts/business.py stats (absolute path).
User arguments: $ARGUMENTS
Procedure
1. Scope and orchestration plan
Enter plan mode before the first edit. In Claude Code call
EnterPlanMode; in Cursor, Codex, or Gemini use /plan or
Shift+Tab. Where plan mode is unavailable, present the plan as text.
Present the plan (shape below) and ask where to write the run,
defaulting per interim-format.md § Where runs live. Write nothing,
including index.md, until the user approves. Exit plan mode, then
open the run at the approved root with business.py init, per
interim-format.md § Where runs live. Pass --date when the request
names a dated run path; if init refuses, follow the same section.
Non-interactive (no question tool, headless): print the plan with the default root and stop. A request that itself names the root approves the plan; record the root in the run README and continue.
Reply in this shape (reply form per interim-format.md § Finished
run), with no greeting, naming roots as the user would type them:
Plan: review-skill, window 2026-04-01..2026-06-30. Nothing is written yet.
## Measure
- Cycle time and first-review latency per PR; rework signals.
- Adoption and per-task timing only from exports you provide.
## Instruments
- git and gh to probe; trackers and timing logs only from exports you provide.
## Output
- 2026-07-14/business/review-skill under ~/Documents, the default root.
- Questions: confirm the root and the repo paths.
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.
- 5d ago Changed · +9 lines cbaf3025d16a
- 8d ago Changed · +36 lines 224db133628d
- 16d ago Changed · -4 lines 1a2d8584d88a
- 1mo ago First seen · 126 lines · 24 tokens per session scan A ba05b9738fb0
research is a skill published in the GitHub repository tony/skills (0 stars, last pushed 3d ago), licensed MIT. It adds 24 tokens to every session and 1,618 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 2026-09-03.
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