forensics
๐ Plug any AI โ โก Boot a Business Strategist, a Project Manager, a Data Analyst, a Research Director โ from one portable workspace. A persistent, structured operating layer that gives AGI-level Autonomy to any agent โ Claude Code, Gemini CLI, Cursor, Codex, any harness. For every AI power user.
Install / Use
npx skills add Auto-Skiller/plugboot --skill forensicsInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
Our assessment of forensics
forensics scores 69/100 on our quality scale, 434th of 659 Automation skills we index.
Its SKILL.md is 7.2 KB long, well organised into 36 sections with 11 code examples: a thorough specification that gives an agent plenty to work with.
It has no GitHub stars yet, so there is no community track record; judge it on its content.
Maintenance, license and trust
- We could not determine when the repository was last updated.
- Our last check on 2026-09-23 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 68/100, with 3 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit โ read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk โ read a skill before letting an agent act on it.
forensics compared with similar skills
All 4 of these similar skills score higher than forensics; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| forensics (this skill)by Auto-Skiller | 69 | 0 | โ | SKILL.md |
| Agent-Reachby Panniantong | 100 | 85.2k | 9d ago | CLAUDE.md |
| rufloby ruvnet | 100 | 73.2k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 83.4k | today | MCP Server |
| Anthropic-Cybersecurity-Skillsby mukul975 | 99 | 33.3k | 24d ago | CLAUDE.md |
Frequently asked questions
- How do I install forensics?
- Run
npx skills add Auto-Skiller/plugboot --skill forensics. The install tabs above show the steps for each supported agent. - Which AI agents does forensics work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is forensics safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 68/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is forensics still maintained?
- We could not determine when the repository was last updated.
Skill content
View source on GitHubForensics Workflow
Post-mortem investigation for failed or stuck Open-workspace workflows. Analyzes git history,
.planning/ artifacts, and file system state to detect anomalies and generate a
structured diagnostic report.
Principle: This is a read-only investigation. Do not modify project files. Only write the forensic report.
Step 1: Get Problem Description
PROBLEM="$ARGUMENTS"
If $ARGUMENTS is empty, ask the user:
"What went wrong? Describe the issue โ e.g., 'autonomous mode got stuck on phase 3', 'execute-phase failed silently', 'costs seem unusually high'."
Record the problem description for the report.
Step 2: Gather Evidence
Collect data from all available sources. Missing sources are fine โ adapt to what exists.
2a. Git History
# Recent commits (last 30)
git log --oneline -30
# Commits with timestamps for gap analysis
git log --format="%H %ai %s" -30
# Files changed in recent commits (detect repeated edits)
git log --name-only --format="" -20 | sort | uniq -c | sort -rn | head -20
# Uncommitted work
git status --short
git diff --stat
Record:
- Commit timeline (dates, messages, frequency)
- Most-edited files (potential stuck-loop indicator)
- Uncommitted changes (potential crash/interruption indicator)
2b. Planning State
Read these files if they exist:
.planning/STATE.mdโ current milestone, phase, progress, blockers, last session.planning/ROADMAP.mdโ phase list with status.planning/config.jsonโ workflow configuration
Extract:
- Current phase and its status
- Last recorded session stop point
- Any blockers or flags
2c. Phase Artifacts
For each phase directory in .planning/phases/*/:
ls .planning/phases/*/
For each phase, check which artifacts exist:
{padded}-PLAN.mdor{padded}-PLAN-*.md(execution plans){padded}-SUMMARY.md(completion summary){padded}-VERIFICATION.md(quality verification){padded}-CONTEXT.md(design decisions){padded}-RESEARCH.md(pre-planning research)
Track: which phases have complete artifact sets vs gaps.
2d. Session Reports
Read .planning/reports/SESSION_REPORT.md if it exists โ extract last session outcomes,
work completed, token estimates.
2e. Git Worktree State
git worktree list
Check for orphaned worktrees (from crashed agents).
Step 3: Detect Anomalies
Evaluate the gathered evidence against these anomaly patterns:
Stuck Loop Detection
Signal: Same file appears in 3+ consecutive commits within a short time window.
# Look for files committed repeatedly in sequence
git log --name-only --format="---COMMIT---" -20
Parse commit boundaries. If any file appears in 3+ consecutive commits, flag as:
- Confidence HIGH if the commit messages are similar (e.g., "fix:", "fix:", "fix:" on same file)
- Confidence MEDIUM if the file appears frequently but commit messages vary
Missing Artifact Detection
Signal: Phase appears complete (has commits, is past in roadmap) but lacks expected artifacts.
For each phase that should be complete:
- PLAN.md missing โ planning step was skipped
- SUMMARY.md missing โ phase was not properly closed
- VERIFICATION.md missing โ quality check was skipped
Abandoned Work Detection
Signal: Large gap between last commit and current time, with STATE.md showing mid-execution.
# Time since last commit
git log -1 --format="%ai"
If STATE.md shows an active phase but the last commit is >2 hours old and there are uncommitted changes, flag as potential abandonment or crash.
Crash/Interruption Detection
Signal: Uncommitted changes + STATE.md shows mid-execution + orphaned worktrees.
Combine:
git statusshows modified/staged files- STATE.md has an active execution entry
git worktree listshows worktrees beyond the main one
Scope Drift Detection
Signal: Recent commits touch files outside the current phase's expected scope.
Read the current phase PLAN.md to determine expected file paths. Compare against files actually modified in recent commits. Flag any files that are clearly outside the phase's domain.
Test Regression Detection
Signal: Commit messages containing "fix test", "revert", or re-commits of test files.
git log --oneline -20 | grep -iE "fix test|revert|broken|regression|fail"
Step 4: Generate Report
Create the forensics directory if needed:
mkdir -p .planning/forensics
Write to .planning/forensics/report-$(date +%Y%m%d-%H%M%S).md:
# Forensic Report
**Generated:** {ISO timestamp}
**Problem:** {user's description}
---
## Evidence Summary
### Git Activity
- **Last commit:** {date} โ "{message}"
- **Commits (last 30):** {count}
- **Time span:** {earliest} โ {latest}
- **Uncommitted changes:** {yes/no โ list if yes}
- **Active worktrees:** {count โ list if >1}
### Planning State
- **Current milestone:** {version or "none"}
- **Current phase:** {number โ name โ status}
- **Last session:** {stopped_at from STATE.md}
- **Blockers:** {any flags from STATE.md}
### Artifact Completeness
| Phase | PLAN | CONTEXT | RESEARCH | SUMMARY | VERIFICATION |
|-------|------|---------|----------|---------|-------------|
{for each phase: name | โ
/โ per artifact}
## Anomalies Detected
### {Anomaly Type} โ {Confidence: HIGH/MEDIUM/LOW}
**Evidence:** {specific commits, files, or state data}
**Interpretation:** {what this likely means}
{repeat for each anomaly found}
## Root Cause Hypothesis
Based on the evidence above, the most likely explanation is:
{1-3 sentence hypothesis grounded in the anomalies}
## Recommended Actions
1. {Specific, actionable remediation step}
2. {Another step if applicable}
3. {Recovery command if applicable โ e.g., `/gsd-resume-work`, `/gsd-execute-phase N`}
---
*Report generated by `/gsd-forensics`. All paths redacted for portability.*
Redaction rules:
- Replace absolute paths with relative paths (strip
$HOMEprefix) - Remove any API keys, tokens, or credentials found in git diff output
- Truncate large diffs to first 50 lines
Step 5: Present Report
Display the full forensic report inline.
Step 6: Offer Interactive Investigation
"Report saved to
.planning/forensics/report-{timestamp}.md.I can dig deeper into any finding. Want me to:
- Trace a specific anomaly to its root cause?
- Read specific files referenced in the evidence?
- Check if a similar issue has been reported before?"
If the user asks follow-up questions, answer from the evidence already gathered. Read additional files only if specifically needed.
Step 7: Offer Issue Creation
If actionable anomalies were found (HIGH or MEDIUM confidence):
"Want me to create a GitHub issue for this? I'll format the findings and redact paths."
If confirmed:
# Check if "bug" label exists before using it
BUG_LABEL=$(gh label list --search "bug" --json name -q '.[0].name' 2>/dev/null)
LABEL_FLAG=""
if [ -n "$BUG_LABEL" ]; then
LABEL_FLAG="--label bug"
fi
gh issue create \
--title "bug: {concise description from anomaly}" \
$LABEL_FLAG \
--body "{formatted findings from report}"
Step 8: Update STATE.md
gsd-sdk query state.record-session "" \
"Forensic investigation complete" \
".planning/forensics/report-{timestamp}.md"
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit โ see the Safety scan above for what the skill file itself contains.
