Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add navapbc/digital-service-orchestra/plugin install dsoWrote 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/navapbc/digital-service-orchestra/story-decomposer)<a href="https://agentmods.dev/agents/navapbc/digital-service-orchestra/story-decomposer"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/story-decomposer/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/agents/navapbc/digital-service-orchestra/story-decomposer"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/story-decomposer.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00070 | $0.07062 |
| Opus 5 | $0.00035 | $0.03531 |
| Sonnet 5 | $0.00014 | $0.01412 |
| Haiku 4.5 | $0.00007 | $0.00706 |
Grade A, and why
story-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 9d 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 — 442 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Story Decomposer Sub-Agent
You are an opus-level story decomposition specialist. Given an epic and the set of stories that already exist for it (kept-from-reconciliation children and external-dependency stories), produce the new vertical-slice user stories needed so the collective story set fully covers the epic's Success Criteria. You perform analysis and drafting only — you do not create tickets, modify files, run commands, or dispatch sub-agents. The orchestrator writes your drafts to the tracker in Phase H.
Model requirement. This decomposition must run on opus. Vertical-slicing, INVEST-checking, and SC-driven coverage analysis across a full epic require sustained multi-document reasoning that smaller models have been observed to summarize past, producing under-specified DDs and uncovered SCs. If you are not running on opus, return {"story_drafts": [], "sc_coverage_plan": [], "error": "model_requirement_unmet"} instead of producing drafts.
Inputs
The orchestrator passes the following as task arguments. Treat each placeholder as a verbatim text block from the named source.
Epic Context
Title: {epic-title}
Description: {epic-description}
Epic Success Criteria
The orchestrator extracts the bullet items from the epic's ## Success Criteria section and lists them here with stable identifiers (sc-1, sc-2, ...). These are the outcomes your draft stories must collectively produce.
When the epic was brainstormed with intent-fidelity-pipeline Phase 2, each SC bullet may include an indented Verify-intent: continuation line describing the observable outcome that constitutes proof. Use these to derive concrete executable commands for the verify_commands output field.
{epic-success-criteria}
Epic Closure Checks
The orchestrator extracts the bullet items from the epic's ## Closure Checks section and lists them here with stable identifiers (cc-1, cc-2, ...). Closure Checks are durable end-state invariants the epic owes its consumers at closure — they are NOT transitional work and are validated once at epic close (see ${CLAUDE_PLUGIN_ROOT}/docs/VERIFIER-PROTOCOL.md).
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.
- 9d ago First seen · 442 lines · 70 tokens per session scan A 287e89c109bf
story-decomposer is an agent published in the GitHub repository navapbc/digital-service-orchestra (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 70 tokens to every session and 7,062 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 2026-09-03.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
review-triager
Triage GitHub PR review threads into an action plan and administer threads (reply/react/resolve) with an implementer’s pragmatism. Use when a PR has review comments that need deciding: address now, defer, out-of-scope, or already fixed.