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 tmchow/tmc-marketplace --skill researchgit clone --depth 1 https://github.com/tmchow/tmc-marketplaceWrote 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/tmchow/tmc-marketplace/research)<a href="https://agentmods.dev/skills/tmchow/tmc-marketplace/research"><img src="https://agentmods.dev/badge/skills/tmchow/tmc-marketplace/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/tmchow/tmc-marketplace/research"><img src="https://agentmods.dev/badge/skills/tmchow/tmc-marketplace/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 | $0.00052 | $0.01524 |
| Opus 5 | $0.00026 | $0.00762 |
| Sonnet 5 | $0.00010 | $0.00305 |
| Haiku 4.5 | $0.00005 | $0.00152 |
Grade A, and why
iterative: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 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.
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Research
Research open questions from a PRD or a user-provided set of questions. Categorize each question, spawn parallel research subagents for investigatable items, synthesize findings, and update the PRD.
This skill resolves unknowns where the answer exists somewhere and needs to be found — prior art, external constraints, codebase patterns, competitive landscape. For unknowns about visual design, UX, or interaction feel, use iterative:design-exploration instead.
When to Use
- After
iterative:brainstormingproduces a PRD with open questions that can be answered through research - When the user has specific questions to investigate before planning
- When scope, requirements, or direction questions need answers before tech planning can proceed
- Can be invoked standalone with a list of questions (no PRD required)
Key Principles
- Categorize before investigating — Not all questions belong here. Technical implementation questions (how to query X, which API to use) belong in tech planning's codebase exploration. Questions about visual design or interaction feel belong in
iterative:design-exploration. This skill handles scope, requirements, external research, and prior art questions. - Parallel research — Spawn independent research subagents for each question. Questions are typically unrelated and benefit from concurrent investigation.
- Update the source of truth — When a PRD exists, findings should update it directly. Answered questions move out of Open Questions; new constraints become requirements.
- Present before committing — Show findings and proposed PRD changes to the user for approval before updating the document.
Workflow
Phase 1: Gather Questions
- If invoked with a PRD path: Read the PRD's Open Questions section. Extract all tagged questions.
- If invoked with user-provided questions: Use the questions as provided.
- If no input: Ask the user for either a PRD path or a set of questions.
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 · 109 lines · 52 tokens per session scan A 1ee4d195596e
iterative:research is a skill published in the GitHub repository tmchow/tmc-marketplace (22 stars, last pushed 6mo ago), licensed MIT. It adds 52 tokens to every session and 1,524 once invoked, about $0.0003 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 2026-08-30.
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