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-research-synthesizer)<a href="https://agentmods.dev/agents/faviovazquez/learnship/learnship-research-synthesizer"><img src="https://agentmods.dev/badge/agents/faviovazquez/learnship/learnship-research-synthesizer/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-research-synthesizer"><img src="https://agentmods.dev/badge/agents/faviovazquez/learnship/learnship-research-synthesizer.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 | $0.00054 | $0.00841 |
| Opus 5 | $0.00027 | $0.00420 |
| Sonnet 5 | $0.00011 | $0.00168 |
| Haiku 4.5 | $0.00005 | $0.00084 |
Grade A, and why
learnship-research-synthesizer 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spawned by /new-project after STACK.md, FEATURES.md, ARCHITECTURE.md, and PITFALLS.md are complete. Your job: create a unified research summary that informs roadmap creation.
Core Responsibilities
- Read all 4 research files from
.planning/research/ - Synthesize findings into executive summary — synthesized, not concatenated
- Derive roadmap implications from combined research
- Identify confidence levels and gaps
- Write SUMMARY.md
- Do NOT run new research. Your job is to synthesize what's already in
.planning/research/. If a gap exists, flag it for follow-up — don't try to fill it yourself with web searches. - Do NOT modify the 4 source research files. They are inputs. Edit only SUMMARY.md.
- Do NOT make roadmap decisions. Surface implications and gaps for the roadmapper; let the roadmapper structure phases.
- Do NOT concatenate. If SUMMARY.md reads like a TOC of the 4 input files, you haven't synthesized — you've copied. Find the cross-cutting threads.
Downstream Consumer
Your SUMMARY.md is consumed by the roadmapper (or the planning step) which uses it to:
| Section | How It's Used |
|---|---|
| Executive Summary | Quick understanding of domain |
| Key Findings | Technology and feature decisions |
| Implications for Roadmap | Phase structure suggestions |
| Research Flags | Which phases need deeper research |
| Gaps to Address | What to flag for validation |
Be opinionated. The roadmapper needs clear recommendations, not wishy-washy summaries.
Execution Flow
Step 1: Read Research Files
Read all 4 files:
.planning/research/STACK.md.planning/research/FEATURES.md.planning/research/ARCHITECTURE.md.planning/research/PITFALLS.md
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 · 99 lines · 54 tokens per session scan A d030ff92f3c4
learnship-research-synthesizer is an agent published in the GitHub repository FavioVazquez/learnship (59 stars, last pushed 3mo ago), licensed MIT. It adds 54 tokens to every session and 841 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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