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 agentmods add skills/nickmisasi/planner/researchnpx skills add nickmisasi/planner --skill researchgit clone --depth 1 https://github.com/nickmisasi/plannerWrote 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/nickmisasi/planner/research)<a href="https://agentmods.dev/skills/nickmisasi/planner/research"><img src="https://agentmods.dev/badge/skills/nickmisasi/planner/research.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.00823 |
| Opus 5 | $0.00018 | $0.00411 |
| Sonnet 5 | $0.00007 | $0.00165 |
| Haiku 4.5 | $0.00004 | $0.00082 |
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 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.
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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conduct a focused research session to inform planning.
Instructions
When the user invokes /research, follow these steps:
1. Ensure Context is Loaded
Research should be tied to a project and ideally an idea. If no context is loaded, trigger /continue first. If the user wants project-level research (not idea-specific), that's fine — results go in context.md.
2. Define Research Scope
Use AskUserQuestion to clarify what we're researching. Options:
- Codebase analysis — Read and understand code in a target repo
- Web research — Look up docs, APIs, libraries, blog posts, technical references
- Product research — Competitive analysis, user patterns, product decisions
- Mixed — Combination of the above
Also ask:
- Specific questions — What exactly do we need to find out?
- Depth — Quick survey or deep dive?
3. Conduct the Research
For codebase analysis:
- Use
ghCLI to browse the target repo (fromproject.yamlrepos list) - Clone if deep analysis is needed:
git clone <url> /tmp/<repo-name> - Use Grep, Glob, and Read tools to navigate
- Focus on architecture, patterns, and relevant code paths
- Note file paths and line numbers for key findings
For web research:
- Use WebSearch and WebFetch tools
- Search for relevant documentation, blog posts, and discussions
- Look for prior art and how others have solved similar problems
- Check library docs, API references, and changelogs
For product research:
- Search for competitive products and how they handle similar features
- Look for user feedback, forum discussions, and feature requests
- Check GitHub issues/discussions on relevant projects
4. Record Findings
Update the appropriate file:
- Idea-level research: Write findings to
projects/<project>/ideas/<idea>/research.md - Project-level research: Write findings to
projects/<project>/context.md
Structure findings clearly:
- Group by topic/question
- Include sources (URLs, file paths, commit hashes)
- Highlight key takeaways
- Note how findings impact the spec or planning
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 First seen · 98 lines · 37 tokens per session scan A a21710fed777
research is a skill published in the GitHub repository nickmisasi/planner (5 stars, last pushed 4mo ago), licensed MIT. It adds 37 tokens to every session and 823 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 2026-08-31.
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