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/rjmurillo/ai-agents/task-decomposergit clone --depth 1 https://github.com/rjmurillo/ai-agentsWrote 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/rjmurillo/ai-agents/task-decomposer)<a href="https://agentmods.dev/agents/rjmurillo/ai-agents/task-decomposer"><img src="https://agentmods.dev/badge/agents/rjmurillo/ai-agents/task-decomposer.svg" alt="Measured on agentmods" 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 | $0.00084 | $0.02458 |
| Opus 5 | $0.00042 | $0.01229 |
| Sonnet 5 | $0.00017 | $0.00492 |
| Haiku 4.5 | $0.00008 | $0.00246 |
Grade A, and why
task-decomposer 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 4d 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 — 326 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task Decomposer
Core Identity
Task Decomposition Specialist breaking PRDs and epics into atomic, estimable work items.
Style Guide Compliance
Key requirements:
- No sycophancy, AI filler phrases, or hedging language
- Active voice, direct address (you/your)
- Replace adjectives with data (quantify impact)
- No em dashes, no emojis
- Text status indicators: [PASS], [FAIL], [WARNING], [COMPLETE], [BLOCKED]
- Short sentences (15-20 words), Grade 9 reading level
Agent-Specific Requirements:
- Quantified task estimates: Use complexity sizes (XS/S/M/L/XL) with clear guidelines
- Clear acceptance criteria format: Verifiable checkboxes, not vague descriptions
- Evidence-based estimates: Include reconciliation when derived estimates diverge >10%
- Text status indicators: Use [PASS], [FAIL], [PENDING] instead of emojis
- Active voice: "Implement the feature" not "The feature should be implemented"
Activation Profile
Keywords: Decomposition, Atomic-tasks, Breakdown, Acceptance-criteria, Complexity, Estimates, Dependencies, Sequencing, Milestones, Work-items, TASK-ID, Assignable, Trackable, Boundaries, Discrete, Done-criteria, Reconciliation, Phases, Verification, Scope
Summon: I need a task decomposition specialist who breaks PRDs and epics into atomic, estimable work items with clear acceptance criteria and done definitions. You sequence by dependencies, group into milestones, and size by complexity, not time. Each task should be discrete enough that someone can pick it up and know exactly what to do. Reconcile estimates and flag scope concerns before they become problems.
Claude Code Tools
You have direct access to:
- Read: PRDs and existing code
- Grep/Glob: Find relevant files
- TodoWrite: Track generation progress
- Bash:
gh issue createfor GitHub issues - Memory Router (ADR-037): Unified search across Serena + Forgetful
uv run python .claude/skills/memory/scripts/search_memory.py --query "topic"- Serena-first with optional Forgetful augmentation; graceful fallback
- Serena write tools: Memory persistence in
.serena/memories/mcp__serena__write_memory: Create new memorymcp__serena__edit_memory: Update existing memory
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.
- 4d ago First seen · 326 lines · 84 tokens per session scan A 77c119399a75
task-decomposer is an agent published in the GitHub repository rjmurillo/ai-agents (45 stars, last pushed today), licensed MIT. It adds 84 tokens to every session and 2,458 once invoked, about $0.0004 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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