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 skills add Jamie-BitFlight/claude_skills --skill task-decompositiongit clone --depth 1 https://github.com/Jamie-BitFlight/claude_skillsWrote 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/skills/jamie-bitflight/claude_skills/task-decomposition)<a href="https://agentmods.dev/skills/jamie-bitflight/claude_skills/task-decomposition"><img src="https://agentmods.dev/badge/skills/jamie-bitflight/claude_skills/task-decomposition/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jamie-bitflight/claude_skills/task-decomposition"><img src="https://agentmods.dev/badge/skills/jamie-bitflight/claude_skills/task-decomposition.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 43 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 5.1 | $0.00066 | $0.02437 |
| Opus 5.5 | $0.00026 | $0.00975 |
| Sonnet 5.5 | $0.00013 | $0.00487 |
| Haiku 4.5 | $0.00007 | $0.00244 |
Grade A, and why
task-decomposition 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 1mo 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 — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SAM Stage 4 — Task Decomposition
Role
You are the task decomposition agent for the SAM pipeline. You break a contextualized plan into atomic tasks that can each be executed by a fresh, stateless agent with zero prior context.
When to Use
- After Stage 3 Context Integration produces a contextualized ARTIFACT:PLAN
- Before Stage 5 Execution dispatches tasks to agents
- When a plan needs to be split into parallelizable work units
Process
flowchart TD
Start([Contextualized ARTIFACT:PLAN]) --> A1[1. Identify atomic work units]
A1 --> A2[2. Embed complete context per task]
A2 --> A3[3. Apply CLEAR ordering]
A3 --> A4{Accuracy risk medium/high?}
A4 -->|Yes| CoVe[4a. Add CoVe checks]
A4 -->|No| A5[4b. Skip CoVe]
CoVe --> A5[5. Map dependencies]
A5 --> A6[6. Assign agents]
A6 --> Gate{Evaluate complexity}
Gate -->|Manageable| Done([Tasks registered in the plan])
Gate -->|High complexity or novel architecture| Escalate([Human touchpoint — confirm decomposition])
Step 1 — Identify Atomic Work Units
Each task must be:
- Atomic — completes one logical change; cannot be meaningfully subdivided
- Independent — executable without asking clarifying questions
- Verifiable — has acceptance criteria provable by the executing agent
- Bounded — clear scope boundaries (what is in, what is out)
Split along natural seams:
- One file or tightly coupled file set per task
- One logical concern per task (do not mix creation with testing)
- Separate infrastructure changes from application logic
Step 2 — Embed Complete Context
The task IS the complete prompt. The executing agent has NO memory of previous stages and reads nothing but what the task carries. Embed everything needed:
- Relevant excerpts from ARTIFACT:PLAN (not "see plan" — inline it)
- File paths and line ranges from contextualization
- Patterns to follow (from resource map)
- Integration points to connect to
- Constraints and anti-goals that apply to this specific task
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.
- 1mo ago Changed · +7 lines 0c5c5200615d
- 1mo ago First seen · 274 lines · 66 tokens per session scan A 98fd4fa4dbf0
task-decomposition is a skill published in the GitHub repository Jamie-BitFlight/claude_skills (67 stars, last pushed 4d ago), licensed MIT. It adds 66 tokens to every session and 2,437 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-06.
Other skills, from other repositories
story-readiness
Checks whether a story is ready to implement: clear acceptance criteria, no open questions, valid ADR and dependencies. Use when the user asks if a story, or the sprint's stories, are ready to start or build.
recipe-create-meet-space
Create a Google Meet meeting space and share the join link.
workthreads
SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…
atmos-config
Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.
qa-project-bootstrap
Onboard a new QA engineer to an existing codebase, or audit an existing test architecture. Produces a 30-day ramp plan: codebase orientation, framework walkthrough, test architecture audit, mentorship pairing, and first-test guidance. Use when: "QA onboarding," "new tester," "ramp up," "test architecture audit,"…
handle-linkedin-connection-request-signal
Use this skill when someone sends a team member an inbound LinkedIn connection request. An inbound request is a deliberate, ACTIVE first-party intent signal — meaningfully stronger than a passive profile view — and it deserves different scoring rules. The skill resolves and enriches the requester, gates them through…