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/fmflurry/settings-opencode/evolvegit clone --depth 1 https://github.com/fmflurry/settings-opencodeWhat 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 | $0.00004 | $0.00566 |
| Opus 5 | $0.00002 | $0.00283 |
| Sonnet 5 | $0.00001 | $0.00113 |
| Haiku 4.5 | $0.00000 | $0.00057 |
Grade A, and why
evolve 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 yesterday.
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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Evolve Command
Cluster related instincts into structured skills: $ARGUMENTS
Your Task
Analyze instincts and promote clusters to skills.
Evolution Process
Step 1: Analyze Instincts
Group instincts by:
- Trigger similarity
- Action patterns
- Category tags
- Confidence levels
Step 2: Identify Clusters
Cluster: Error Handling
├── Instinct: Catch specific errors (0.85)
├── Instinct: Wrap errors with context (0.82)
├── Instinct: Log errors with stack trace (0.78)
└── Instinct: Return meaningful error messages (0.80)
Step 3: Generate Skill
When cluster has:
- 3+ instincts
- Average confidence > 0.75
- Cohesive theme
Generate SKILL.md:
# Error Handling Skill
## Overview
Patterns for robust error handling learned from session observations.
## Patterns
### 1. Catch Specific Errors
**Trigger**: When catching errors with generic catch
**Action**: Use specific error types
### 2. Wrap Errors with Context
**Trigger**: When re-throwing errors
**Action**: Add context with fmt.Errorf or Error.cause
### 3. Log with Stack Trace
**Trigger**: When logging errors
**Action**: Include stack trace for debugging
### 4. Meaningful Messages
**Trigger**: When returning errors to users
**Action**: Provide actionable error messages
Step 4: Archive Instincts
Move evolved instincts to archived/ with reference to skill.
Evolution Report
Evolution Summary
=================
Clusters Found: X
Cluster 1: Error Handling
- Instincts: 5
- Avg Confidence: 0.82
- Status: ✅ Promoted to skill
Cluster 2: Testing Patterns
- Instincts: 3
- Avg Confidence: 0.71
- Status: ⏳ Needs more confidence
Cluster 3: Git Workflow
- Instincts: 2
- Avg Confidence: 0.88
- Status: ⏳ Needs more instincts
Skills Created:
- skills/error-handling/SKILL.md
Instincts Archived: 5
Remaining Instincts: 12
Thresholds
| Metric | Threshold |
|---|---|
| Min instincts per cluster | 3 |
| Min average confidence | 0.75 |
| Min cluster cohesion | 0.6 |
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.
- yesterday First seen · 113 lines · 4 tokens per session scan A 36c1e79a362f
evolve is a command published in the GitHub repository fmflurry/settings-opencode (172 stars, last pushed 19d ago), licensed MIT. It adds 4 tokens to every session and 566 once invoked, about $0.0000 per session on Opus 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.