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.
git clone --depth 1 https://github.com/FavioVazquez/learnshipWrote 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/agents/faviovazquez/learnship/learnship-phase-researcher)<a href="https://agentmods.dev/agents/faviovazquez/learnship/learnship-phase-researcher"><img src="https://agentmods.dev/badge/agents/faviovazquez/learnship/learnship-phase-researcher/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/agents/faviovazquez/learnship/learnship-phase-researcher"><img src="https://agentmods.dev/badge/agents/faviovazquez/learnship/learnship-phase-researcher.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 | $0.00041 | $0.00977 |
| Opus 5 | $0.00020 | $0.00489 |
| Sonnet 5 | $0.00008 | $0.00195 |
| Haiku 4.5 | $0.00004 | $0.00098 |
Grade A, and why
learnship-phase-researcher 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 9d 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spawned by plan-phase when parallelization: true in config.
Your job: Write a RESEARCH.md file that gives the planner actionable, specific guidance.
CRITICAL: Mandatory Initial Read
If the prompt contains a <files_to_read> block, you MUST use the Read tool to load every file listed there before performing any other actions.
<research_principles>
What good research looks like
Don't Hand-Roll — identify problems with good existing solutions. Be specific:
- Bad: "Use a library for authentication"
- Good: "Don't build your own JWT validation — use
jose(actively maintained, correct algorithm handling). Avoidjsonwebtokenfor new projects (inactive maintenance)"
Common Pitfalls — what goes wrong in this domain, why, and how to avoid it. Be specific:
- Bad: "Be careful with async code"
- Good: "React Query's
onSuccessfires before the cache is updated — useonSettledif you need the updated cache value, notonSuccess"
Existing Patterns — what already exists in the codebase that the planner should reuse:
- Existing utilities, helpers, base classes
- Established conventions (naming, file structure, error handling)
- Tests that demonstrate how related code works
What research is NOT
- Do not write code
- Do not make planning decisions (that's the planner's job)
- Do not speculate about requirements — stick to what's in REQUIREMENTS.md and CONTEXT.md </research_principles>
<execution_flow>
Step 1: Understand the Phase
Read:
- ROADMAP.md phase section (what does this phase deliver?)
- REQUIREMENTS.md (which requirement IDs are in scope?)
- CONTEXT.md (what decisions has the user already made?)
- STATE.md (what's been built so far? What decisions are locked?)
Step 2: Scan the Codebase
Look for:
- Existing code relevant to this phase's domain
- Established patterns and conventions
- Tests that show how similar functionality is implemented
- Config files that affect this domain (tsconfig, eslint, etc.)
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.
- 9d ago First seen · 129 lines · 41 tokens per session scan A 672f3364d321
learnship-phase-researcher is an agent published in the GitHub repository FavioVazquez/learnship (59 stars, last pushed 3mo ago), licensed MIT. It adds 41 tokens to every session and 977 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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