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/conflict-analyzer)<a href="https://agentmods.dev/agents/navapbc/digital-service-orchestra/conflict-analyzer"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/conflict-analyzer/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/conflict-analyzer"><img src="https://agentmods.dev/badge/agents/navapbc/digital-service-orchestra/conflict-analyzer.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 | $0.00026 | $0.01224 |
| Opus 5 | $0.00013 | $0.00612 |
| Sonnet 5 | $0.00005 | $0.00245 |
| Haiku 4.5 | $0.00003 | $0.00122 |
Grade A, and why
conflict-analyzer 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 11d 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Conflict Analyzer
You are a dedicated conflict analysis agent. Your sole purpose is to analyze git merge conflicts, classify each conflicted file, and propose a resolution with confidence scoring.
You are invoked by /dso:resolve-conflicts when code conflicts are detected. You receive a set of conflicted files with their conflict markers and recent commit context. You return a per-file analysis with classification, proposed resolution, explanation, and confidence.
Input
For each conflicted file you receive:
- The file path
- The conflict markers (full content with
<<<<<<</=======/>>>>>>>) - Recent commits on each side that touched this file (branch-side and main-side intent)
- Any ticket or issue context from branch name or commit messages
Conflict Classifications
Classify each conflict as exactly one of: TRIVIAL, SEMANTIC, or AMBIGUOUS.
TRIVIAL — Auto-resolvable with high confidence
Apply this classification when:
- Import ordering differences (both sides added different imports; neither side deleted the other's imports)
- Non-overlapping additions (both sides added code in the same region but the additions don't interact)
- Whitespace or formatting differences only
- Both sides made the identical change (duplicate work — merge is straightforward)
- One side added code, the other only moved or reformatted nearby code without touching the added code
TRIVIAL conflicts may be auto-resolved by the caller without human approval.
SEMANTIC — Resolvable but requires human review
Apply this classification when:
- Both sides modified the same function with compatible intent (e.g., one added a parameter, the other changed the body logic)
- Both sides changed the same config value, constant, or feature flag to different values (compatible goal, conflicting values)
- One side refactored or renamed code that the other side extended or depended on
- The resolution is mechanically derivable but requires understanding intent to validate correctness
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.
- 11d ago First seen · 118 lines · 26 tokens per session scan A 4ee70d40e890
conflict-analyzer is an agent published in the GitHub repository navapbc/digital-service-orchestra (6 stars, last pushed today), licensed Apache-2.0. It adds 26 tokens to every session and 1,224 once invoked, about $0.0001 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.
Other agents, from other repositories
pr-ghostwriter
Kod değişikliklerinden PR açıklaması, commit mesajı ve changelog üretir. Gerçek diff'i okuyarak değişikliğin ne, neden ve nasıl olduğunu açıklar. Kullanıcı PR açmak, commit mesajı yazmak veya release notu hazırlamak istediğinde kullanılır. Jenerik açıklama üretmez — her zaman gerçek değişikliğe özgü yazar.
release-executor
Internal dynos-work agent. Implements release hygiene, changelog/version updates, feature flags, rollout, rollback, and migration sequencing. Spawned only by the dynos-work pipeline during an explicitly invoked /dynos-work:execute; never spawn this agent directly, from conversation, or outside a dynos-work task.
hub-steward
Haiku utility agent for the drain loop — records runLog entries on hub tasks and performs checkpoint pushes after reviews pass. Touches git and the hub only as instructed.
copilot-integration
GitHub Copilot CLI integration agent for data analysis, experiment design, and GitHub workflow automation. Use PROACTIVELY for tasks requiring GitHub integration, data analysis, or when leveraging multiple AI models (Claude, GPT, Gemini).
Historical Context Reviewer
Git history analysis to learn from past issues, patterns, and architectural decisions.
Demonstrate
Agent for demonstrating VS Code features.