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 Jeffallan/writing-with-agents --skill research-intakegit clone --depth 1 https://github.com/Jeffallan/writing-with-agentsWrote 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/jeffallan/writing-with-agents/research-intake)<a href="https://agentmods.dev/skills/jeffallan/writing-with-agents/research-intake"><img src="https://agentmods.dev/badge/skills/jeffallan/writing-with-agents/research-intake/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/jeffallan/writing-with-agents/research-intake"><img src="https://agentmods.dev/badge/skills/jeffallan/writing-with-agents/research-intake.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 | $0.00037 | $0.01965 |
| Opus 5 | $0.00018 | $0.00983 |
| Sonnet 5 | $0.00007 | $0.00393 |
| Haiku 4.5 | $0.00004 | $0.00197 |
Grade A, and why
research-intake 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 13d 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role Definition
The Research Intake specialist traverses, indexes, and maps source material into a structured knowledge map before any content creation begins.
Lead: AI traverses and indexes source material, builds the knowledge map, identifies gaps. Support: Human steers gap-filling priorities, validates the map, and seeds with context about what matters.
This skill handles Obsidian vault files, markdown notes, reference documents, prior research, and web URLs. It assumes arbitrary nested file and folder structures with no predetermined naming conventions or organizational schemes. The skill does not assume Zettelkasten, PARA, or any other specific note-taking methodology.
The knowledge map is a structured inventory of what the research corpus contains, what it lacks, and how its pieces connect. It is not an outline or a content plan -- those belong to downstream skills.
When to Use This Skill
- Starting a writing project and need to understand what material already exists
- Ingesting an Obsidian vault, folder of markdown notes, or collection of reference documents
- Building a research corpus from scattered sources before content planning
- Identifying what gaps exist in existing research before generating new material
- Preparing source material for handoff to the content-strategist or madman phase
- Auditing a knowledge base to understand coverage and depth across topics
- Onboarding to a new domain where prior research exists but is unorganized
- Combining multiple research sources into a unified understanding
- Returning to a dormant project and need to rediscover what research already exists
- Validating that source material has enough depth to support a planned content calendar
- Cross-referencing claims across multiple documents to find contradictions or reinforcement
- Preparing for a content audit where you need to map what topics are already covered and to what depth
- Triaging a large collection of notes to determine which are relevant to a specific writing project
What ships with it
2 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.
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.
- 13d ago First seen · 128 lines · 37 tokens per session scan A e6abdf4676c0
research-intake is a skill published in the GitHub repository Jeffallan/writing-with-agents (31 stars, last pushed 2mo ago), licensed MIT. It adds 37 tokens to every session and 1,965 once invoked, about $0.0002 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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