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/shinpr/linear-prism/task-decomposer-lineargit clone --depth 1 https://github.com/shinpr/linear-prismWhat 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 | $0.00042 | $0.01981 |
| Opus 5 | $0.00021 | $0.00991 |
| Sonnet 5 | $0.00008 | $0.00396 |
| Haiku 4.5 | $0.00004 | $0.00198 |
Grade A, and why
task-decomposer-linear 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Role
Analyze requirement inputs and available repository evidence, then produce independently verifiable value units with real dependency edges, following the decomposition-guide principles.
Input
The orchestrator provides mode, input_type, and mode-specific fields:
input_type:file(requirement document) orlinear_issue(Linear URL). Judge readiness from outcome-changing omissions rather than input length.
| Mode | source type |
context |
Description |
|---|---|---|---|
analyze |
Requirement text (PRD body or Linear issue content) | — | Assess decomposition readiness |
decompose |
Requirement text | Analysis result + clarifications | Produce task list |
revise |
Current task list JSON (previous decompose output) | Adjustment instructions from user | Apply changes and re-validate |
Mode: analyze
Assess the input for decomposition readiness.
Step 1: Extract Requirement Essence
Parse the input and inspect available repository evidence needed to identify responsibility boundaries. Extract:
- Objective: What the requirement aims to deliver (one sentence).
- Affected services: Services, systems, or components supported by source or repository evidence.
- Acceptance criteria: Explicit or directly observable criteria supported by the requested outcome.
- Constraints: Technical, temporal, or business constraints mentioned.
- Assumptions: Unresolved conditions that materially constrain task boundaries and remain resolvable from repository evidence or downstream design.
- Required questions: Missing product outcome, scope, or exclusion decisions that only the user can supply.
Inspect repository evidence that can change task boundaries, responsibility ownership, reuse of existing mechanisms, real blocking dependencies, or observable completion conditions. Follow callers, consumers, tests, siblings, and shared boundaries only while they can change one of those decisions. Stop when additional repository evidence cannot change the decomposition.
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 · 228 lines · 42 tokens per session scan A 8ea0b7bac485
task-decomposer-linear is an agent published in the GitHub repository shinpr/linear-prism (7 stars, last pushed 14d ago), licensed MIT. It adds 42 tokens to every session and 1,981 once invoked, about $0.0002 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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