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 commands/with-geun/alive-analysis/analysis-retrogit clone --depth 1 https://github.com/with-geun/alive-analysisWrote 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/commands/with-geun/alive-analysis/analysis-retro)<a href="https://agentmods.dev/commands/with-geun/alive-analysis/analysis-retro"><img src="https://agentmods.dev/badge/commands/with-geun/alive-analysis/analysis-retro.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 | $0.01443 |
| Opus 5 | $0.00000 | $0.00722 |
| Sonnet 5 | $0.00000 | $0.00289 |
| Haiku 4.5 | $0.00000 | $0.00144 |
Grade A, and why
analysis-retro 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 5d 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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/analysis retro
Generate an automatic retrospective report from archived analyses.
Instructions
Step 1: Parse period parameters
Check the user's arguments:
--last-month(default) — previous calendar month--last-quarter— previous 3 calendar months--range {from} {to}— custom range (e.g.,--range 2026-01 2026-03)--all— all archived analyses
If no arguments provided, default to --last-month.
Tell the user: "Generating retrospective for {period}. Scanning archives..."
Step 2: Scan archived analyses
Read all analyses in analyses/archive/{YYYY-MM}/ folders within the specified period.
For each analysis, extract:
- ID and title (from folder/file name)
- Type: Investigation / Modeling / Simulation (from file header or ASK stage)
- Mode: Full / Quick
- Tags (from file header or status.md)
- Key Insight (from summary.md or EVOLVE one-sentence insight)
- Confidence levels (from VOICE: count of 🟢/🟡/🔴)
- Impact Tracking table (from EVOLVE):
- Each recommendation's Decision (Accepted/Rejected/Modified/Pending)
- Each recommendation's Status (Not started/In progress/Done)
- Outcome notes
- Follow-up proposals (from EVOLVE "Follow-up Analyses" section)
- Duration (from ID date to archive date)
Also scan analyses/active/ for any follow-up analyses that reference archived ones.
Step 3: Generate retro report
Create the file at analyses/.retro/retro_{period}.md (e.g., retro_2026-02.md or retro_2026-Q1.md).
Create the .retro/ directory inside analyses/ if it doesn't exist.
Use this template:
# Analysis Retrospective — {Period}
> Generated: {today}
> Scope: {N} analyses from {period}
---
## Summary
{2-3 sentence overview of the period's analysis activity, major themes, and key outcomes.}
---
## Analysis Activity
| Metric | Count |
|--------|-------|
| Total analyses | {N} |
| Full | {n} |
| Quick | {n} |
| Investigation 🔍 | {n} |
| Modeling 📈 | {n} |
| Simulation 🔮 | {n} |
Average duration: {X} days (Full), {X} days (Quick)
---
## Impact Tracking
### Decision Outcomes
| Status | Count | % |
|--------|-------|---|
| ✅ Accepted | {n} | {%} |
| ❌ Rejected | {n} | {%} |
| 🔄 Modified | {n} | {%} |
| ⏳ Pending | {n} | {%} |
### Top Wins
{List the recommendations that were Accepted + Done with positive outcomes. Max 5.}
1. **{ID}** — {Recommendation} → {Outcome}
2. ...
### Unresolved Items
{List recommendations still Pending or Not Started.}
- {ID} Rec #{n}: "{recommendation}" — {status}
- ...
---
## Patterns
### Recurring Topics
{Topics/tags that appeared in 3+ analyses.}
| Topic | Analyses | Key Trend |
|-------|----------|-----------|
| {tag} | {count} | {one-line summary of how findings evolved} |
### Common Findings
{Findings that appear across multiple analyses — convergent evidence.}
- {Finding shared by IDs}
### Confidence Distribution
| Level | Count | % |
|-------|-------|---|
| 🟢 High | {n} | {%} |
| 🟡 Medium | {n} | {%} |
| 🔴 Low | {n} | {%} |
{If 🔴 Low > 30%: "High proportion of low-confidence findings. Consider investing in better data infrastructure or longer analysis timelines."}
---
## Unresolved Follow-ups
{EVOLVE sections propose follow-up analyses. List those that haven't been started yet.}
| Source | Proposed Follow-up | Status |
|--------|--------------------|--------|
| {ID} | {follow-up question} | 🟡 Not started / ✅ Started as {new-ID} |
{If >50% unstarted: "Most follow-up proposals haven't been acted on. Consider prioritizing the top 2-3 as next analyses."}
---
## Recommendations
Based on this retrospective:
1. **{Recommendation}**: {Explanation with supporting data}
2. **{Recommendation}**: {Explanation}
3. **{Recommendation}**: {Explanation}
{Generate 2-4 recommendations based on the patterns above. Examples:}
{- If a topic recurs: "Consolidate retention insights into a meta-analysis"}
{- If follow-ups are neglected: "Schedule dedicated follow-up time each sprint"}
{- If impact tracking is sparse: "Improve impact tracking discipline — only 30% of recommendations have outcomes recorded"}
{- If confidence is mostly 🔴: "Invest in data quality or longer timelines for higher-confidence analysis"}
---
## Appendix — Full Analysis List
| # | ID | Title | Type | Mode | Tags | Key Insight | Impact |
|---|-----|-------|------|------|------|-------------|--------|
| 1 | {ID} | {title} | {type} | {mode} | {tags} | {insight} | {Accepted/Rejected/Pending} |
| 2 | ... | ... | ... | ... | ... | ... | ... |
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.
- 5d ago First seen · 176 lines · 0 tokens per session scan A f47be439eb80
analysis-retro is a command published in the GitHub repository with-geun/alive-analysis (41 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,443 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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