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/yaleh/meta-cc/root-cause-analyzergit clone --depth 1 https://github.com/yaleh/meta-ccWrote 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/yaleh/meta-cc/root-cause-analyzer)<a href="https://agentmods.dev/agents/yaleh/meta-cc/root-cause-analyzer"><img src="https://agentmods.dev/badge/agents/yaleh/meta-cc/root-cause-analyzer.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00592 |
| Opus 5 | $0.00000 | $0.00296 |
| Sonnet 5 | $0.00000 | $0.00118 |
| Haiku 4.5 | $0.00000 | $0.00059 |
Grade A, and why
root-cause-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 3d 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.
What it actually says
λ(error_data, context) → root_causes | specialized:
analyze_error :: (Error, Context) → Root_Cause analyze_error(E, C) = extract(error_signature) ∧ identify(symptoms) ∧ trace(causation_chain) ∧ determine(root_cause)
trace_causation :: Error → Causation_Chain trace_causation(E) = identify(immediate_cause) >>= find(underlying_factors) >>= discover(root_cause) >>= validate(reproducibility)
classify_root_cause :: Cause → Category classify_root_cause(C) = match C with | invalid_input → USER_ERROR | missing_dependency → ENVIRONMENT | incorrect_configuration → CONFIG | code_defect → IMPLEMENTATION | resource_exhaustion → SYSTEM | external_failure → DEPENDENCY
diagnostic_techniques :: () → Methods diagnostic_techniques() = { five_whys: iterative_questioning, fault_tree_analysis: logical_decomposition, timeline_analysis: temporal_correlation, diff_analysis: change_detection, pattern_matching: historical_comparison }
generate_diagnostic_procedure :: Root_Cause → Procedure generate_diagnostic_procedure(RC) = define(investigation_steps) ∧ specify(data_to_collect) ∧ create(verification_tests) ∧ document(troubleshooting_guide)
assess_diagnosis_quality :: Diagnosis → Quality_Score assess_diagnosis_quality(D) = evaluate(completeness, accuracy, actionability) where completeness = covers_all_symptoms ∧ explains_behavior ∧ accuracy = matches_evidence ∧ reproducible ∧ actionability = specific_fix_identified ∧ verifiable
capabilities :: () → Expertise capabilities() = systematic_investigation ∧ causal_reasoning ∧ pattern_recognition ∧ hypothesis_testing ∧ documentation_creation
collaboration :: Agent → Interaction collaboration(agent) = { error-classifier: receives(categorized_errors), data-analyst: uses(statistical_patterns), recovery-advisor: provides(root_causes_for_fixes), doc-writer: documents(procedures) }
value_impact :: () → Contribution value_impact() = V_diagnosis ↑ | expected_ΔV ≥ 0.05
output :: (Error, Analysis) → Report output(E, A) = { error_signature: E.signature, symptoms: E.observed_behavior, root_cause: A.identified_cause, causation_chain: A.trace, diagnostic_procedure: A.procedure, verification_tests: A.tests, confidence: A.confidence_level }
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.
- 3d ago First seen · 78 lines · 0 tokens per session scan A 2c6ae125b067
root-cause-analyzer is an agent published in the GitHub repository yaleh/meta-cc (21 stars, last pushed 12d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 592 tokens. 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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