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/gustavobarbosab/sage/codegit clone --depth 1 https://github.com/gustavobarbosab/sageWhat 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 | $0.00384 |
| Opus 5 | $0.00000 | $0.00192 |
| Sonnet 5 | $0.00000 | $0.00077 |
| Haiku 4.5 | $0.00000 | $0.00038 |
Grade A, and why
code 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.
What it actually says
/sage code
Generates production-ready code from spec.md + behavior.md.
Gate check (REQUIRED before generating)
Read behavior.md and check for unresolved open questions (- [ ] items).
If any - [ ] items remain:
⚠️ Cannot generate code — open questions remain in behavior.md:
• <question 1>
• <question 2>
Mark each question resolved with [x] in behavior.md, then run /sage code again.
Stop. Do not generate any code.
Only proceed when all open questions are marked [x] or removed.
Instructions
Read:
- Harness (
.sage/harness.md,CLAUDE.md,.cursorrules, or project knowledge) spec.mdbehavior.md(all resolved scenarios)
Generate production-ready code that:
- Follows harness conventions EXACTLY — stack, naming patterns, architecture, restrictions
- Implements every acceptance criterion from spec.md
- Satisfies every scenario in behavior.md with corresponding test code
- Includes previews/examples where the harness requires them
- Respects every "Do NOT" item from spec.md
Output format
Return files in this format — each file preceded by its path:
// FILE: <relative/path/to/File.kt>
<file content>
// FILE: <relative/path/to/FileTest.kt>
<file content>
Do not include explanations between files unless asked. Do not deviate from the harness architecture.
After generation
Tell the user:
"Code generated. Review it against the acceptance criteria in spec.md — point by point, not by gut feel. Use /sage update <feedback> for any changes needed. When it's ready, run /sage pr and /sage doc to export."
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 · 62 lines · 0 tokens per session scan A 408843140432
code is a command published in the GitHub repository gustavobarbosab/sage (2 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 384 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 2026-08-31.
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.