autopsy

Name: autopsy
Author: Rune-kit

80stars21forks

How to install autopsy?

rune-kit/rune/autopsy

$npx -y skills add Rune-kit/rune --skill autopsy

Installs into the current project.

Summary

Full codebase health assessment. Use when diagnosing project health or starting a rescue workflow on legacy code — OR when evaluating an external GitHub repo for dependency / fork / contribution decisions (--external mode). Analyzes complexity, dependencies, dead code, tech debt,

Files · 1

View on GitHub

SKILL.md

1	# autopsy
2
3	## Purpose
4
5	Full codebase health assessment for legacy projects. Autopsy analyzes complexity, dependency coupling, dead code, tech debt, and git hotspots to produce a health score per module and a prioritized rescue plan. Uses opus for deep analysis quality.
6
7	## Called By (inbound)
8
9	- `rescue` (L1): Phase 0 RECON — assess damage before refactoring
10	- `onboard` (L2): when project appears messy during onboarding
11	- `audit` (L2): Phase 3 code quality and complexity assessment
12	- `incident` (L2): root cause analysis after containment
13
14	## Calls (outbound)
15
16	- `scout` (L2): deep structural scan — files, LOC, entry points, imports
17	- `research` (L3): identify if tech stack is outdated
18	- `trend-scout` (L3): compare against current best practices
19	- `journal` (L3): record health assessment findings
20
21	## Execution Steps
22
23	### Step 0 — Repo intelligence (if GitHub-hosted)
24
25	If the project is a GitHub repository, gather repo-level metrics before diving into code:
26
27	```bash
28	# Fetch via GitHub API (requires gh CLI or curl + GITHUB_TOKEN)
29	gh api repos/{owner}/{repo} --jq '{stars: .stargazers_count, forks: .forks_count, open_issues: .open_issues_count, license: .license.spdx_id, language: .language, topics: .topics, created: .created_at, pushed: .pushed_at}'
30
31	# Contributor count and top contributors
32	gh api repos/{owner}/{repo}/contributors --jq 'length'
33	gh api repos/{owner}/{repo}/contributors --jq '.[0:5] \| .[] \| "\(.login): \(.contributions)"'
34
35	# Commit frequency (last 52 weeks)
36	gh api repos/{owner}/{repo}/stats/commit_activity --jq '[.[] \| .total] \| add'
37
38	# Language byte distribution
39	gh api repos/{owner}/{repo}/languages
40	```
41
42	Record in working notes:
43	- Activity signal: commits/week (>5 = active, 1-5 = maintained, <1 = stale)
44	- Bus factor: contributor count (1 = critical risk, 2-3 = low, >5 = healthy)
45	- Community signal: stars/forks ratio, open issue count, staleness of latest push
46
47	Skip this step for local-only projects with no remote.
48
49	### Step 1 — Structure scan
50
51	Call `rune:scout` with a request for a full project map. Ask scout to return:
52	- All source files with LOC counts
53	- Entry points and main modules
54	- Import/dependency graph (who imports who)
55	- Test files and their coverage targets
56	- Config files (tsconfig, eslint, package.json, etc.)
57
58	### Step 2 — Module analysis
59
60	For each major module identified by scout, use `Read` to open the file and assess:
61	- LOC (flag anything over 500 as a god file)
62	- Function count and average function length
63	- Maximum nesting depth (flag > 4 levels)
64	- Cyclomatic complexity signals (deep conditionals, many branches)
65	- Test file presence and estimated coverage
66
67	Record findings per module in a working table.
68
69	### Step 3 — Health scoring
70
71	Score each module 0-100 across six dimensions:
72
73	\| Dimension \| Weight \| Scoring criteria \|
74	\|---\|---\|---\|
75	\| Complexity \| 20% \| Cyclomatic < 5 = 100, 5-10 = 70, 10-20 = 40, > 20 = 0 \|
76	\| Test coverage \| 25% \| > 80% = 100, 50-80% = 60, 20-50% = 30, < 20% = 0 \|
77	\| Documentation \| 15% \| README + inline comments = 100, partial = 50, none = 0 \|
78	\| Dependencies \| 20% \| Low coupling = 100, medium = 60, high/circular = 0 \|
79	\| Code smells \| 10% \| No god files, no deep nesting = 100, each violation -20 \|
80	\| Maintenance \| 10% \| Regular commits = 100, stale > 6 months = 50, untouched > 1yr = 0 \|
81
82	Compute weighted score per module. Assign risk tier:
83	- 80-100 = healthy (green)
84	- 60-79 = watch (yellow)
85	- 40-59 = at-risk (orange)
86	- 0-39 = critical (red)
87
88	### Step 4 — Risk assessment
89
90	Use `Bash` to gather git archaeology data:
91
92	```bash
93	# Most changed files (hotspots)
94	git log --format=format: --name-only \| sort \| uniq -c \| sort -rg \| head -20
95
96	# Files not touched in over a year
97	git log --before="1 year ago" --format="%H" \| head -1 \| xargs -I{} git diff --name-only {}..HEAD
98
99	# Authors per file (high author count = high churn risk)
100	git log --format="%an" -- <file> \| sort -u \| wc -l
101
102	# Commit velocity by month (trend detection)
103	git log --format="%Y-%m" \| sort \| uniq -c \| tail -12
104
105	# Issue/PR close rate (GitHub only)
106	gh api repos/{owner}/{repo}/issues --jq '[.[] \| select(.pull_request == null)] \| length'
107	```
108
109	Identify:
110	- Circular dependencies (A imports B, B imports A)
111	- God files (> 500 LOC with many importers)
112	- Hotspot files (changed most often = highest bug density)
113	- Dead files (no importers, no recent commits)
114	- Velocity trend: accelerating, stable, or decelerating (compare last 3 months)
115
116	### Step 5 — Generate RESCUE-REPORT.md
117
118	Use `Write` to save `RESCUE-REPORT.md` at the

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Type

autopsy

80stars21forks

View on GitHub

How to install autopsy?

rune-kit/rune/autopsy

$npx -y skills add Rune-kit/rune --skill autopsy

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# autopsy
2
3	## Purpose
4
5	Full codebase health assessment for legacy projects. Autopsy analyzes complexity, dependency coupling, dead code, tech debt, and git hotspots to produce a health score per module and a prioritized rescue plan. Uses opus for deep analysis quality.
6
7	## Called By (inbound)
8
9	- `rescue` (L1): Phase 0 RECON — assess damage before refactoring
10	- `onboard` (L2): when project appears messy during onboarding
11	- `audit` (L2): Phase 3 code quality and complexity assessment
12	- `incident` (L2): root cause analysis after containment
13
14	## Calls (outbound)
15
16	- `scout` (L2): deep structural scan — files, LOC, entry points, imports
17	- `research` (L3): identify if tech stack is outdated
18	- `trend-scout` (L3): compare against current best practices
19	- `journal` (L3): record health assessment findings
20
21	## Execution Steps
22
23	### Step 0 — Repo intelligence (if GitHub-hosted)
24
25	If the project is a GitHub repository, gather repo-level metrics before diving into code:
26
27	```bash
28	# Fetch via GitHub API (requires gh CLI or curl + GITHUB_TOKEN)
29	gh api repos/{owner}/{repo} --jq '{stars: .stargazers_count, forks: .forks_count, open_issues: .open_issues_count, license: .license.spdx_id, language: .language, topics: .topics, created: .created_at, pushed: .pushed_at}'
30
31	# Contributor count and top contributors
32	gh api repos/{owner}/{repo}/contributors --jq 'length'
33	gh api repos/{owner}/{repo}/contributors --jq '.[0:5] \| .[] \| "\(.login): \(.contributions)"'
34
35	# Commit frequency (last 52 weeks)
36	gh api repos/{owner}/{repo}/stats/commit_activity --jq '[.[] \| .total] \| add'
37
38	# Language byte distribution
39	gh api repos/{owner}/{repo}/languages
40	```
41
42	Record in working notes:
43	- Activity signal: commits/week (>5 = active, 1-5 = maintained, <1 = stale)
44	- Bus factor: contributor count (1 = critical risk, 2-3 = low, >5 = healthy)
45	- Community signal: stars/forks ratio, open issue count, staleness of latest push
46
47	Skip this step for local-only projects with no remote.
48
49	### Step 1 — Structure scan
50
51	Call `rune:scout` with a request for a full project map. Ask scout to return:
52	- All source files with LOC counts
53	- Entry points and main modules
54	- Import/dependency graph (who imports who)
55	- Test files and their coverage targets
56	- Config files (tsconfig, eslint, package.json, etc.)
57
58	### Step 2 — Module analysis
59
60	For each major module identified by scout, use `Read` to open the file and assess:
61	- LOC (flag anything over 500 as a god file)
62	- Function count and average function length
63	- Maximum nesting depth (flag > 4 levels)
64	- Cyclomatic complexity signals (deep conditionals, many branches)
65	- Test file presence and estimated coverage
66
67	Record findings per module in a working table.
68
69	### Step 3 — Health scoring
70
71	Score each module 0-100 across six dimensions:
72
73	\| Dimension \| Weight \| Scoring criteria \|
74	\|---\|---\|---\|
75	\| Complexity \| 20% \| Cyclomatic < 5 = 100, 5-10 = 70, 10-20 = 40, > 20 = 0 \|
76	\| Test coverage \| 25% \| > 80% = 100, 50-80% = 60, 20-50% = 30, < 20% = 0 \|
77	\| Documentation \| 15% \| README + inline comments = 100, partial = 50, none = 0 \|
78	\| Dependencies \| 20% \| Low coupling = 100, medium = 60, high/circular = 0 \|
79	\| Code smells \| 10% \| No god files, no deep nesting = 100, each violation -20 \|
80	\| Maintenance \| 10% \| Regular commits = 100, stale > 6 months = 50, untouched > 1yr = 0 \|
81
82	Compute weighted score per module. Assign risk tier:
83	- 80-100 = healthy (green)
84	- 60-79 = watch (yellow)
85	- 40-59 = at-risk (orange)
86	- 0-39 = critical (red)
87
88	### Step 4 — Risk assessment
89
90	Use `Bash` to gather git archaeology data:
91
92	```bash
93	# Most changed files (hotspots)
94	git log --format=format: --name-only \| sort \| uniq -c \| sort -rg \| head -20
95
96	# Files not touched in over a year
97	git log --before="1 year ago" --format="%H" \| head -1 \| xargs -I{} git diff --name-only {}..HEAD
98
99	# Authors per file (high author count = high churn risk)
100	git log --format="%an" -- <file> \| sort -u \| wc -l
101
102	# Commit velocity by month (trend detection)
103	git log --format="%Y-%m" \| sort \| uniq -c \| tail -12
104
105	# Issue/PR close rate (GitHub only)
106	gh api repos/{owner}/{repo}/issues --jq '[.[] \| select(.pull_request == null)] \| length'
107	```
108
109	Identify:
110	- Circular dependencies (A imports B, B imports A)
111	- God files (> 500 LOC with many importers)
112	- Hotspot files (changed most often = highest bug density)
113	- Dead files (no importers, no recent commits)
114	- Velocity trend: accelerating, stable, or decelerating (compare last 3 months)
115
116	### Step 5 — Generate RESCUE-REPORT.md
117
118	Use `Write` to save `RESCUE-REPORT.md` at the

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Type