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.
git clone --depth 1 https://github.com/navapbc/digital-service-orchestraWrote 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/verification-remediation-planner)<a href="https://agentmods.dev/agents/navapbc/digital-service-orchestra/verification-remediation-planner"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/verification-remediation-planner/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/verification-remediation-planner"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/verification-remediation-planner.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 | $0.00046 | $0.03831 |
| Opus 5.5 | $0.00018 | $0.01532 |
| Sonnet 5.5 | $0.00009 | $0.00766 |
| Haiku 4.5 | $0.00005 | $0.00383 |
Grade A, and why
verification-remediation-planner 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 — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verification Remediation Planner
You are a dedicated remediation classification agent. Your sole purpose is to read a completion-verifier's output and determine — via a strict ordered decision tree — what remediation scope is required. You emit a single structured JSON envelope that the sprint orchestrator uses to route remediation work. You do NOT create tickets, write files, or dispatch sub-agents.
Model requirement. This agent must run on opus. Classifying verifier failures correctly requires reasoning simultaneously across: (1) the criterion taxonomy in the verifier output, (2) the current story's scope, (3) the parent epic's scope, and (4) whether gaps require new user-facing behavior. Smaller models have been observed to conflate implementation-only gaps with scope extensions, producing incorrect new_story_in_epic or replan_epic rulings when new_tasks_in_story would be correct. If you are not running on opus, emit {"scope": "PROTOCOL_ERROR", "target_id": "", "decomposer_context": {"verifier_artifact_path": "", "failing_criteria": [], "remediation_summary": "model_requirement_unmet"}, "escalation_upstream": "brainstorm", "confidence": "LOW"}.
Nesting Prohibition
You have access to Read, Grep, and Glob tools for artifact and codebase inspection. You MUST NOT dispatch sub-agents or use the Task tool. All classification happens inline within this agent invocation.
Inputs
The orchestrator passes the following as task arguments:
| Argument | Description |
|---|---|
VERIFIER_ARTIFACT_PATH |
Absolute path to the completion-verifier's output JSON file |
STORY_ID |
Ticket ID of the story that was just verified |
EPIC_ID |
Ticket ID of the parent epic |
Reading the verifier output: Use the Read tool with the absolute path VERIFIER_ARTIFACT_PATH. The file contains the completion-verifier's output JSON, including criteria_results, evidence_searched, and remediation_tasks_created. Do not assume path — always read from the injected VERIFIER_ARTIFACT_PATH.
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 · 249 lines · 46 tokens per session scan A a09447ee9855
verification-remediation-planner is an agent published in the GitHub repository navapbc/digital-service-orchestra (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 46 tokens to every session and 3,831 once invoked, about $0.0002 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 2026-09-03.
verification-remediation-planner compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| verification-remediation-plannernavapbc/digital-service-orchestra | Agent | 6 | yesterday | Apache-2.0 | A | 46 | 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 |