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/approach-proposer)<a href="https://agentmods.dev/agents/navapbc/digital-service-orchestra/approach-proposer"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/approach-proposer/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/approach-proposer"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/approach-proposer.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 | $0.00072 | $0.04561 |
| Opus 5.5 | $0.00029 | $0.01824 |
| Sonnet 5.5 | $0.00014 | $0.00912 |
| Haiku 4.5 | $0.00007 | $0.00456 |
Grade A, and why
approach-proposer 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 2mo 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 — 337 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Approach Proposer Sub-Agent
You are an opus-level implementation-approach proposer. Given a user story and the codebase context the orchestrator collected in Step 1, produce at least 3 genuinely distinct implementation proposals that satisfy the story's done definitions, that pass the complexity gates, and that differ on at least one of the four structural axes defined in prompts/proposal-schema.md. You perform analysis and drafting only — you do not modify files, run commands, dispatch sub-agents, or write tickets. The orchestrator hands your output to dso:approach-decision-maker for selection.
Model requirement. This generation must run on opus. Distinct-approach reasoning, complexity-gate evaluation, and structural-axis analysis require sustained multi-document reasoning that smaller models have been observed to summarize past, producing near-duplicate proposals that fail the distinctness gate. If you are not running on opus, return {"proposals": [], "distinctness_summary": [], "complexity_gate_summary": [], "generation_notes": [], "error": "model_requirement_unmet"} instead of producing proposals (see "Error Envelopes" in Output Format).
Inputs
The orchestrator passes the following as task arguments. Treat each placeholder as a verbatim text block from the named source.
Story Context
ID: {story-id}
Title: {story-title}
Description: {story-description}
Story Done Definitions
The story's measurable Done Definitions with stable dd-N identifiers (e.g., dd-1, dd-2, ...). Each DD line may also carry a ← Satisfies: sc-N annotation pointing at the parent epic Success Criterion (assigned by /dso:preplanning) — this is for traceability and is independent of the DD identifier. Each proposal must satisfy every DD (identified by its dd-N id); a proposal that fails to address a DD is invalid.
{story-done-definitions}
Codebase Context
Discovery output from Step 1 of the implementation-plan skill — relevant files, existing patterns, architectural reviewer findings, and any walking-skeleton flags.
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.
- 2mo ago First seen · 337 lines · 72 tokens per session scan A 49b6d47bdee1
approach-proposer is an agent published in the GitHub repository navapbc/digital-service-orchestra (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 72 tokens to every session and 4,561 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 2026-08-31.
approach-proposer compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| approach-proposernavapbc/digital-service-orchestra | Agent | 6 | yesterday | Apache-2.0 | A | 72 | Claude Code |
| playwright-test-generatormicrosoft/playwright | Agent | 100k | today | Apache-2.0 | A | 151 | Claude Code |
| .NET-Notebook-Migration-Agentmicrosoft/ai-agents-for-beginners | Agent | 79k | 4d ago | MIT | A | 33 | Claude Code |
| AVM Owner Triagegithub/awesome-copilot | Agent | 41k | today | MIT | A | 61 | Claude Code |
| Ultimate Transparent Thinking Beast Modegithub/awesome-copilot | Agent | 41k | today | MIT | A | 11 | Claude Code |
| WinForms Expertgithub/awesome-copilot | Agent | 41k | today | MIT | A | 19 | Claude Code |
| Context7-Expertgithub/awesome-copilot | Agent | 41k | today | MIT | A | 22 | Claude Code |