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 coreyhaines31/makerskills --skill deep-researchgit clone --depth 1 https://github.com/coreyhaines31/makerskillsWrote 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/coreyhaines31/makerskills/deep-research)<a href="https://agentmods.dev/skills/coreyhaines31/makerskills/deep-research"><img src="https://agentmods.dev/badge/skills/coreyhaines31/makerskills/deep-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/coreyhaines31/makerskills/deep-research"><img src="https://agentmods.dev/badge/skills/coreyhaines31/makerskills/deep-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Agent Snooping · line 31 Skill reads from agent configuration directories (.claude/, .codex/, .gemini/). These directories may contain API keys, personal settings, and other credentials that the skill has no legitimate need to access.Fix: Remove all code or instructions that access agent configuration directories (.claude/, .codex/, .gemini/). If configuration values are needed, pass them explicitly as parameters or environment variabl
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 | $0.00221 | $0.01428 |
| Opus 5.5 | $0.00088 | $0.00571 |
| Sonnet 5.5 | $0.00044 | $0.00286 |
| Haiku 4.5 | $0.00022 | $0.00143 |
Grade A, and why
deep-research scanned grade A with 1 finding 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 3d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| Specific URLs | When the user hands over starting URLs | Your agent's URL fetch (e.g. `WebFetch`), or `curl` + `defuddle` | How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/deep-research — Multi-source research with archive
Plans, executes, and synthesizes research from multiple sources. Archives the output so the corpus compounds.
Step 1 — Frame the question
Restate the research question in one tight sentence. If ambiguous, ask the user:
- What's the decision this research will inform?
- What's the minimum useful answer? (Saves over-researching.)
- Any sources to prioritize or avoid?
Output: **Research question:** <one sentence>
Step 2 — Plan the sources
Pick from this menu based on the question type. Note which sources you'll hit and why.
| Source | When to use | How (tool names vary by agent) |
|---|---|---|
| Web search (Google) | Authoritative articles, docs, official statements | Your agent's web search (e.g. WebSearch in Claude Code) |
/last30days |
What people are actually saying right now — Reddit, X, YouTube, HN, web recency | The last30days skill, if installed. Otherwise skip it and note the gap |
| Specific URLs | When the user hands over starting URLs | Your agent's URL fetch (e.g. WebFetch), or curl + defuddle |
| Browsable pages (auth-walled, JS-heavy) | Pricing pages, product tours, profiles | agent-browser CLI (any agent with a shell) |
| Memory | Prior research / decisions / context the user already captured | your agent's memory, or grep ${MAKERSKILLS_MEMORY:-${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/memory}/ |
| Notion | If the topic touches a known Notion workspace | Direct Notion API (key in $NOTION_API_KEY, see reference_notion_api.md) |
| Research archive | Prior /deep-research runs that touched this topic |
grep ${MAKERSKILLS_CONFIG:-$HOME/.config/makerskills}/deep-research/archive/ |
Run discovery passes in parallel where possible. Sequential only when one source needs another's output (e.g., agent-browser a URL discovered by web search).
Step 3 — Execute discovery
Run each chosen source. For each result, capture:
- The source (URL or system)
- 1–3 sentence summary of what was said
- Date / recency
- Confidence in the source (high/medium/low)
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.
- 3d ago Changed · +21 tokens per session 1aecd4bdcf2b
- 17d ago Changed · -1 tokens per session scan B → A 589aa4e0c1a3
- 1mo ago First seen · 123 lines · 201 tokens per session scan B 6a37f3c72457
deep-research is a skill published in the GitHub repository coreyhaines31/makerskills (874 stars, last pushed 3d ago), licensed MIT. It adds 221 tokens to every session and 1,428 once invoked, about $0.0009 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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