Borrowing it
Nothing to install: this file belongs to elevanaltd/HestAI-MCP. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/elevanaltd/HestAI-MCP/main/.claude/skills/rccafp/SKILL.mdgit clone --depth 1 https://github.com/elevanaltd/HestAI-MCPWrote 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/skills/elevanaltd/hestai-mcp/rccafp)<a href="https://agentmods.dev/skills/elevanaltd/hestai-mcp/rccafp"><img src="https://agentmods.dev/badge/skills/elevanaltd/hestai-mcp/rccafp/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/skills/elevanaltd/hestai-mcp/rccafp"><img src="https://agentmods.dev/badge/skills/elevanaltd/hestai-mcp/rccafp.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 | $0.00049 | $0.00742 |
| Opus 5.5 | $0.00020 | $0.00297 |
| Sonnet 5.5 | $0.00010 | $0.00148 |
| Haiku 4.5 | $0.00005 | $0.00074 |
Grade A, and why
rccafp 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 1mo 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RCCAFP - Root Cause, Corrective Action, and Future Proofing
Structured 5-phase incident management protocol for multi-agent AI systems with human orchestration oversight.
When to Use
Trigger RCCAFP when:
- A system constraint violation is detected
- An agent operates outside its role boundaries (overreach)
- A production failure or regression occurs
- A constitutional principle (I1-I6) is violated
- An assumption cascade causes unexpected behavior
- Post-mortem analysis is requested
Five-Phase Process
Phase 1: Detection and Triage
- Create incident directory:
.hestai/state/incidents/YYYYMMDD-[incident-name]/ - Create subdirectories:
01-root-cause/,02-corrective-action/,03-future-proof/ - Document initial symptoms and severity assessment
- Determine if full RCCAFP is warranted vs minor fix
Phase 2: Root Cause Investigation
- Collect evidence: exact causality chains, artifacts, logs
- Cross-validate through multi-agent assessment
- Document in
01-root-cause/causality-chain.md - Identify which system boundaries were violated
Phase 3: Corrective Action
- Immediate containment and mitigation
- Constraint validation - identify gaps in existing boundaries
- Execute triage and damage control
- Document in
02-corrective-action/constraint-validations.mdandtriage-execution.md
Phase 4: Future Proofing
- Extract architectural learnings from the incident
- Design prevention mechanisms with evidence
- Define monitoring requirements
- Document in
03-future-proof/prevention-mechanisms.md
Phase 5: Closure and Integration
- Verify all phases are complete and documented
- Pass findings through synthesis gate before integration
- Update system documentation only after review
- Refine protocol based on learnings
Agent Roles in RCCAFP
| Agent | RCCAFP Role |
|---|---|
| Holistic Orchestrator | Orchestrates process, owns gap accountability |
| Critical Engineer | Leads root cause investigation (tactical) |
| Principal Engineer | Leads future proofing (strategic prevention) |
| Implementation Lead | Executes corrective action implementations |
| Requirements Steward | Validates learnings against North Star |
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.
- 1mo ago First seen · 86 lines · 49 tokens per session scan A cb783592373a
rccafp is a skill published in the GitHub repository elevanaltd/HestAI-MCP (0 stars, last pushed 11d ago), licensed Apache-2.0. It adds 49 tokens to every session and 742 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 2026-08-31.
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