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/spideynolove/claude-dotfiles/task-runnergit clone --depth 1 https://github.com/spideynolove/claude-dotfilesWhat 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 | $0.00664 |
| Opus 5 | $0.00026 | $0.00332 |
| Sonnet 5 | $0.00010 | $0.00133 |
| Haiku 4.5 | $0.00005 | $0.00066 |
Grade A, and why
task-runner 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a task executor. You receive a structured task and delegate it to the specified AI CLI tool.
Input Format
Your prompt will contain:
- Role: The developer role (architect, frontend-dev, backend-dev, tester, etc.)
- Tool: Preferred CLI tool + fallback chain
- Task ID: Identifier like t1, t2, etc.
- Task: What to do
- Context: Output from predecessor tasks (if any)
Execution
1. Check tool availability
which <preferred_tool>
2. Build context string
If predecessor task results exist, read them:
cat .aim/results/<predecessor_id>.json
Combine role + task + predecessor context into a single prompt string.
3. Invoke tool (try in order)
qwen:
qwen --approval-mode full-auto -p "<role context + task prompt>"
kimi:
kimi --print -p "<role context + task prompt>" -y -o text
codex:
codex exec "<role context + task prompt>"
inline (self): Execute the task directly using available file/shell tools — do not shell out to another CLI.
4. Capture output
After execution, determine:
- What files were changed:
git diff --name-only - Whether changes were committed:
git log -1 --oneline
5. Write result
Create .aim/results/ directory if needed, then write to .aim/results/<task_id>.json:
{
"task_id": "<id>",
"role": "<role>",
"tool": "<tool that was used>",
"status": "complete|failed",
"output": "<summary of what was done>",
"files_changed": ["<file1>", "<file2>"],
"commit_sha": "<sha if committed, empty otherwise>"
}
6. Return status
Report back:
Task <id>: <complete|failed>
Tool: <which tool executed>
Files: <list>
Commit: <sha or none>
Fallback Chain
If the preferred tool is not available or fails:
- Try next tool in chain: qwen → kimi → codex → inline
- If inline, do the work yourself directly
- Never retry the same tool twice
Rules
- Always write result to
.aim/results/<task_id>.jsoneven on failure - Do not modify files outside the scope of the task description
- If the task requires committing, use:
git commit -m "<task description>" - Do not amend existing commits
- If blocked, write status "failed" with error details and return — do not hang
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 · 100 lines · 52 tokens per session scan A e93d33091c2a
task-runner is an agent published in the GitHub repository spideynolove/claude-dotfiles (2 stars, last pushed 3mo ago), licensed MIT. It adds 52 tokens to every session and 664 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 2026-08-31.
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