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 commands/fradser/dotclaude/startgit clone --depth 1 https://github.com/FradSer/dotclaudeWhat 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 | $0.00052 | $0.01499 |
| Opus 5 | $0.00026 | $0.00749 |
| Sonnet 5 | $0.00010 | $0.00300 |
| Haiku 4.5 | $0.00005 | $0.00150 |
Grade A, and why
start 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Autoresearch Start (autonomous)
Turn the user's free-text goal in $ARGUMENTS into a complete research contract by inspecting the repo, then grill the contract with the user (one decision at a time, each with a recommended answer) before launching the loop. A wrong contract — especially a wrong evaluator — wastes the whole overnight run, so the contract is a shared decision, not an inference. Any explicit flag the user passed in $ARGUMENTS (e.g. --edit, --score-cmd) is an OVERRIDE — the user already decided that field; use it verbatim and do not re-infer or re-grill it.
Phase 1: Read the goal
The leading free text of $ARGUMENTS (before any --flag) is the GOAL. Record any override flags the user passed.
Empty goal is a refusal. If $ARGUMENTS is empty or whitespace-only, STOP and ask the user for the goal — a loop with no goal has no contract, and every later decision hangs off it.
Phase 2: Infer the contract from the repo
Inspect the repo (list files; read package.json / Makefile / pyproject.toml / README) and derive recommendations for every field (the grill in Phase 3 turns each into a decision):
--edit— the artifact to optimize. If the goal names a file or area, use it. Prefer a SINGLE file when the goal is about one thing — a single file unlocks the tournament escalation.- An evaluator — prefer an OBJECTIVE one; a wrong evaluator wastes the whole run:
- The goal implies a measurable number and a command prints it →
--score-cmd '<cmd>'+--direction min|max. - Else the project has a test/check command (
package.jsonscripts.test/lint/typecheck, a Makefile target,pytest,cargo test) and the goal is "make it work / keep it passing" →--check-cmd '<cmd>'(a pass/fail gate). - Else the goal is qualitative (clarity, readability, prose, design) →
--rubric '<criteria distilled from the goal>', ANCHORED by a--check-cmd(a test/build that must keep passing). NEVER a rubric without a--score-cmdor--check-cmdanchor — a judge-only loop reward-hacks (the setup will refuse it). - Combine when it fits (gate + score, or gate + rubric).
- The goal implies a measurable number and a command prints it →
--objective— a one-line measurable restatement of the goal (what success means).- Bounds — default
--max-experiments 20, unless the goal implies time ("overnight" → `--max-wall-clock 8h"). - TAG — a short slug from the goal (optional; defaults to the date). No need to ask — it is internal.
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 · 62 lines · 52 tokens per session scan A 6e17692a37fd
start is a command published in the GitHub repository FradSer/dotclaude (587 stars, last pushed 20d ago), licensed MIT. It adds 52 tokens to every session and 1,499 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.