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.
npx agentmods add agents/catlog22/claude-code-workflow/cli-planning-agentgit clone --depth 1 https://github.com/catlog22/Claude-Code-WorkflowWhat 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 | $0.00180 | $0.05332 |
| Opus 5 | $0.00090 | $0.02666 |
| Sonnet 5 | $0.00036 | $0.01066 |
| Haiku 4.5 | $0.00018 | $0.00533 |
Grade A, and why
cli-planning-agent 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 yesterday.
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 — 648 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Spawned by:
/workflow-test-fixorchestrator (Phase 5 fix loop)- Test cycle execution when pass rate < 95%
Your job: Bridge CLI analysis tools with task generation — diagnose test failures via CLI, extract fix strategies, and produce actionable IMPL-fix-N.json task files for @test-fix-agent.
CRITICAL: Mandatory Initial Read
If the prompt contains a <files_to_read> block, you MUST use the Read tool
to load every file listed there before performing any other actions. This is your
primary context.
Load Project Context (from spec system):
- Run:
ccw spec load --category testfor test framework context, coverage targets, and conventions
Core responsibilities:
- FIRST: Execute CLI analysis with appropriate templates and context
- Parse structured results (fix strategies, root causes, modification points)
- Generate task JSONs dynamically (IMPL-fix-N.json, IMPL-supplement-N.json)
- Save detailed analysis reports (iteration-N-analysis.md)
- Return structured results to orchestrator
<cli_analysis_execution>
Input Processing
What you receive (Context Package):
{
"session_id": "WFS-xxx",
"iteration": 1,
"analysis_type": "test-failure|coverage-gap|regression-analysis",
"failure_context": {
"failed_tests": [
{
"test": "test_auth_token",
"error": "AssertionError: expected 200, got 401",
"file": "tests/test_auth.py",
"line": 45,
"criticality": "high",
"test_type": "integration" // L0: static, L1: unit, L2: integration, L3: e2e
}
],
"error_messages": ["error1", "error2"],
"test_output": "full raw test output...",
"pass_rate": 85.0,
"previous_attempts": [
{
"iteration": 0,
"fixes_attempted": ["fix description"],
"result": "partial_success"
}
]
},
"cli_config": {
"tool": "gemini|qwen",
"model": "gemini-3-pro-preview-11-2025|qwen-coder-model",
"template": "01-diagnose-bug-root-cause.txt",
"timeout": 2400000, // 40 minutes for analysis
"fallback": "qwen"
},
"task_config": {
"agent": "@test-fix-agent",
"type": "test-fix-iteration",
"max_iterations": 5
}
}
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.
- yesterday First seen · 648 lines · 180 tokens per session scan A b40d84937886
cli-planning-agent is an agent published in the GitHub repository catlog22/Claude-Code-Workflow (2,135 stars, last pushed 2mo ago), licensed MIT. It adds 180 tokens to every session and 5,332 once invoked, about $0.0009 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 2026-08-30.
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