An automated diagnostic skill that synthesizes messy operational logs and state snapshots into structured, evidence-led incident reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install incident-dossier
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install incident-dossier using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Incident Dossier?
The Incident Dossier skill is designed for high-stakes operational environments where speed and accuracy are critical during a post-mortem or active investigation. It empowers AI agents to process diverse evidence sets—including JSON/JSONL audit trails, log files, and state snapshots—into a cohesive Markdown dossier. By utilizing this within the Openclaw Skills framework, developers can move away from manual log parsing and toward structured root cause analysis.
This skill prioritizes technical truth by enforcing an evidence-first approach. It ensures that every generated timeline and blast radius assessment is rooted in parsed artifacts, providing a reliable foundation for engineering teams to assess regressions, queue anomalies, or stuck jobs without getting lost in raw data noise.
Incident Dossier Use Cases
- Investigating system failures and production regressions.
- Analyzing duplicate events or stuck jobs in message queues.
- Auditing JSON/JSONL logs to identify security or consistency anomalies.
- Generating blast radius reports for stakeholders during or after an incident.
- Synthesizing state snapshots into a chronological timeline for debugging.
How Incident Dossier Works
- Evidence Identification: The agent identifies all relevant data sources, such as log files, audit trails, and state snapshots.
- Artifact Parsing: Instead of manual reading, the agent utilizes structured parsing for all JSON/JSONL sources to ensure data integrity.
- Dossier Compilation: The
build_incident_dossier.jsscript is executed with multiple input paths to aggregate findings. - Verification: The generated timeline is cross-referenced against raw log samples to ensure accuracy.
- Reporting: A finalized Markdown dossier is emitted, containing the incident summary, hypotheses, and recommended next actions.
Incident Dossier Setup
To integrate this capability into your workflow, ensure the script is available in your local environment and run it via Node.js as part of the Openclaw Skills suite:
node skills/incident-dossier/scripts/build_incident_dossier.js \
--input path/to/audit.jsonl \
--input path/to/report.json \
--out out/incident-dossier.md
Incident Dossier Data Schema & Taxonomy
The skill produces a structured Markdown document following a strict output contract:
| Section | Description |
|---|---|
| Incident Summary | High-level overview of the event. |
| Scope / Blast Radius | Identification of affected systems and users. |
| Timeline | Chronological list of events with verified timestamps. |
| Evidence List | Reference to all files and logs used in the generation. |
| Hypotheses | Data-backed theories on the likely root cause. |
| Recovery Status | Current state of the system and mitigation efforts. |
| Next Actions | Concrete steps for permanent resolution. |
Incident Dossier Advanced Features
- Multi-Source Aggregation: Ability to combine mixed JSON and JSONL evidence files into a single unified report.
- Uncertainty Flagging: Automatically states uncertainty if timestamps are missing or conflicting rather than fabricating data.
- Evidence-First Logic: Enforces a strict boundary between observed facts and post-incident interpretation.
- Openclaw Skills Integration: Optimized for use with AI coding agents to automate the tedious parts of site reliability engineering (SRE).
SKILL.md
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