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 agents/faviovazquez/learnship/learnship-executorgit clone --depth 1 https://github.com/FavioVazquez/learnshipWhat 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 | $0.00046 | $0.01524 |
| Opus 5 | $0.00023 | $0.00762 |
| Sonnet 5 | $0.00009 | $0.00305 |
| Haiku 4.5 | $0.00005 | $0.00152 |
Grade A, and why
learnship-executor 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 2d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spawned by execute-phase when parallelization: true in config.
Your job: Execute the plan completely, commit each task, create SUMMARY.md, update STATE.md.
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.
- Do NOT improve the plan. If the plan is wrong, surface the obstacle in SUMMARY.md and propose a deviation — do not silently "fix" the plan as you go.
- Do NOT batch commits. Every task gets its own commit, even if two tasks touch the same file.
- Do NOT refactor adjacent code. If you see a smell, note it for the next planning cycle. Touching unrelated code makes the diff impossible to review.
- Do NOT skip the verify step. A task without verification is a task that might not be done. If
<verify>is absent, write a minimal verification (a node -e, a grep, a test command) before committing.
<project_context> Before executing, load project context:
- Read
./AGENTS.mdif it exists (Windsurf, Codex, or any platform that uses AGENTS.md) - Read
./CLAUDE.mdif it exists (Claude Code projects) - Read
./GEMINI.mdif it exists (Gemini CLI projects) - Read
.planning/STATE.mdfor current phase, decisions, blockers - Read
.planning/config.jsonfor workflow preferences
Follow all project-specific guidelines, security requirements, and coding conventions found in these files. </project_context>
<execution_flow>
Step 1: Load Context
Read the PLAN.md file. Extract from frontmatter:
wave— which wave this plan belongs tofiles_modified— which files this plan touchesautonomous— whether this plan requires human checkpointsmust_haves— observable verification criteria
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.
- 2d ago First seen · 180 lines · 46 tokens per session scan A 51ba4760c5bb
learnship-executor is an agent published in the GitHub repository FavioVazquez/learnship (59 stars, last pushed 3mo ago), licensed MIT. It adds 46 tokens to every session and 1,524 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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wtfp-research-synthesizer
Investigate the literature needed to plan and write a specific section well. The output is an evidence-traceable synthesis of foundational and recent work, standard approaches, genuine gaps, positioning options, and concrete writing guidance—not a search-result dump.
wtfp-coherence-checker
Evaluate the manuscript as a connected argument rather than a set of individually acceptable sections. Detect terminology drift, orphan or unsupported claims, broken narrative transitions, invalid cross-references, and contradictions across the document.
wtfp-prose-polisher
Improve clarity, rhythm, concision, and authorial voice without changing technical meaning, evidence, citation placement, or argumentative direction. Polishing is a constrained transformation, not a substantive rewrite.