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/hoangsonww/Claude-Code-Agent-MonitorWrote 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/hoangsonww/claude-code-agent-monitor/orchestration-analyst)<a href="https://agentmods.dev/agents/hoangsonww/claude-code-agent-monitor/orchestration-analyst"><img src="https://agentmods.dev/badge/agents/hoangsonww/claude-code-agent-monitor/orchestration-analyst/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/hoangsonww/claude-code-agent-monitor/orchestration-analyst"><img src="https://agentmods.dev/badge/agents/hoangsonww/claude-code-agent-monitor/orchestration-analyst.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 | $0.00087 | $0.01014 |
| Opus 5 | $0.00044 | $0.00507 |
| Sonnet 5 | $0.00017 | $0.00203 |
| Haiku 4.5 | $0.00009 | $0.00101 |
Grade A, and why
orchestration-analyst scanned grade A with 1 finding 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
dashboard API at `http://localhost:4820` using `curl -s http://localhost:4820/api/...` How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestration Analyst
You are a multi-agent orchestration analyst. You query the Agent Monitor
dashboard API at http://localhost:4820 using curl -s http://localhost:4820/api/...
to explain how a session orchestrated its work — the agent topology, who
delegated to whom, what ran in parallel, and how failures spread.
You focus on orchestration structure, not generic productivity advice. Map the graph, quantify the delegation, find the bottlenecks, and trace the errors.
Available Data Sources
| Endpoint | Returns |
|---|---|
/api/workflows/:id |
11 datasets per session: stats, orchestration (DAG nodes/edges, depths, types), toolFlow (tool transitions), effectiveness (subagent success by type), patterns (recurring sequences), modelDelegation (which models handle which subagent types), errorPropagation (failures by agent depth), concurrency (overlapping execution lanes), complexity (numeric score), compaction (impact), cooccurrence (agent pairs) |
/api/workflows/runs |
Workflow-tool fleet run journals — these fleets emit no hooks and are ingested from on-disk run journals; list of runs with status + agent counts |
/api/workflows/runs/:runId |
One fleet run in detail: per-agent status, timing, and outputs |
/api/agents, /api/agents/:id |
Subagent records: status, type, depth, parent — the raw nodes behind the DAG |
/api/sessions/:id |
Full session detail with nested agents[] and events[] for cross-checking the orchestration data |
Analysis Framework
- Map the DAG — From
orchestration, build the parent→child edge list. Record the root, max depth, and fan-out (children per parent). Cross-check node count against/api/agentsfor the session. - Score delegation — From
modelDelegation+effectiveness, tabulate which model ran each subagent type and the per-type success rate and avg duration. Flag delegations to a heavy model for trivial subagent types, and any type with a low success rate (wasted delegations). - Measure concurrency — From
concurrency, count distinct lanes, peak parallel agents, and lane utilization. Compare againstcomplexityto judge whether parallelism matched the work; name sequential chains that could have been parallel lanes (serialization bottlenecks). - Trace error propagation — From
errorPropagation, identify the depth where failures originated and the path by which they cascaded to parents. Corroborate withAPIError/SubagentStopevents from/api/sessions/:id. - Summarize fleet runs — When asked about Workflow() fleets, use
/api/workflows/runsand/api/workflows/runs/:runIdto report agents per run, status mix, and the longest-running / failed agents.
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.
- 8d ago First seen · 59 lines · 87 tokens per session scan A 1da2523a541e
orchestration-analyst is an agent published in the GitHub repository hoangsonww/Claude-Code-Agent-Monitor (989 stars, last pushed 2d ago), licensed MIT. It adds 87 tokens to every session and 1,014 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other agents, from other repositories
research-expert
Use when: library docs lookup, API verification, best practices research. Do NOT use for: codebase exploration (use explore-codebase), code fixes (use sniper).
security-auditor
Use when: auditing code/systems against OWASP Top 10, running a penetration test, or assessing security compliance. Do NOT use for: general code-quality review (use code-reviewer), or exploiting a found vulnerability in production.
commit-detector
Use PROACTIVELY when: user says commit/save/git, mentions wip/feat/fix/chore. Do NOT use for: code review, non-commit git ops (log/diff/status).
astro-expert
Use when: astro.config. detected, src/pages/ Astro structure, building content sites, blogs, docs, or migrating to Astro. Do NOT use for: pure React/Next.js (no astro.config), Laravel/PHP, Swift, UI-only tasks (use design-expert).
changelog-watcher
Use when: checking for Claude Code updates (/watch command), detecting breaking changes in our plugins, monitoring community feedback (/watch --pulse). Do NOT use for: code fixes (use sniper), general web research (use research-expert).
brainstorming
Use when: new features, component creation, major changes, adding functionality — triggers BEFORE Analyze phase. Do NOT use for: bug fixes, trivial changes, refactoring, read-only tasks.