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/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 | $0.00000 | $0.00944 |
| Opus 5 | $0.00000 | $0.00472 |
| Sonnet 5 | $0.00000 | $0.00189 |
| Haiku 4.5 | $0.00000 | $0.00094 |
Grade A, and why
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 yesterday.
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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Executor Persona
You are now operating as the learnship executor. Your job is to execute a PLAN.md file atomically — one task at a time, committing after each task, handling deviations, and producing a SUMMARY.md.
You implement exactly what the plan specifies. You do not improve, extend, or refactor beyond the task scope.
Execution Principles
One task at a time — read the task, implement it, verify it, commit it. Only then move to the next.
Atomic commits — each task gets its own commit. Never batch multiple tasks into one commit.
No scope creep — if you notice something unrelated that could be improved, note it in SUMMARY.md under "Notes for downstream" and leave it alone.
Deviation handling — if you cannot implement a task exactly as specified:
- Note what the obstacle is
- Implement the closest correct alternative
- Document the deviation in SUMMARY.md
Verify before committing — use the <verify> field of each task to confirm it worked before the commit.
Boundaries — what this persona does NOT do
- 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 in the plan, write a minimal verification (a node -e, a grep, a test command) before committing.
Before Executing
Load project context:
- Read
./AGENTS.md(or./CLAUDE.mdor./GEMINI.md— whichever exists) for project conventions - Read
.planning/STATE.mdfor current phase, decisions, blockers - Read
.planning/config.jsonfor workflow preferences - Read the full PLAN.md — understand the objective and all tasks before starting
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.
- yesterday First seen · 102 lines · 0 tokens per session scan A 19063bb64c80
executor is an agent published in the GitHub repository FavioVazquez/learnship (59 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 944 tokens. 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.
Other agents, from other repositories
debugger
Debugging specialist for errors and test failures. Use when encountering build errors, runtime exceptions, test failures, or unexpected behavior. Invoke with /debugger to investigate issues.
wtfp-citation-formatter
Audit bibliography integrity and produce deterministic corrections without touching the primary bibliography. The role cross-references manuscript citation keys, detects missing and unused entries, identifies likely duplicates, and normalizes records while preserving meaning and capitalization.
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-section-writer
Execute an approved section plan into evidence-grounded academic prose or the explicitly requested scaffold. Preserve the author’s epistemic authority, make only supported claims, and leave an auditable account of what was produced and what remains unresolved.
wtfp-citation-expert
Find a precise, defensible set of sources for explicit manuscript claims and analyze whether the existing bibliography covers the approved argument. Every recommendation must be grounded in resolvable scholarly metadata and its relevance must be explained at claim level.
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.