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 skills/travisennis/acai/compoundingnpx skills add travisennis/acai --skill compoundinggit clone --depth 1 https://github.com/travisennis/acaiWhat 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 | $0.00018 | $0.00551 |
| Opus 5 | $0.00009 | $0.00275 |
| Sonnet 5 | $0.00004 | $0.00110 |
| Haiku 4.5 | $0.00002 | $0.00055 |
Grade A, and why
compounding 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 2d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Compounding Skill
Analyzes the current session to identify self-improvement opportunities for acai.
When to Use
Invoke this skill at the end of a session when:
- The session revealed gaps in acai's knowledge or capabilities
- Tool descriptions caused confusion or misuse
- Repeated patterns suggest a new tool or workflow would help
- Errors occurred that indicate systemic issues
Analysis Process
1. Session Analysis
Review the current session messages in context for patterns indicating improvement opportunities:
- System prompt gaps: Missing context, unclear instructions, assumptions that failed
- Tool description issues: Unclear parameters, missing edge cases, confusing descriptions
- Repeated tool patterns: Same tool sequences used repeatedly (potential new tool)
- Error patterns: Tool failures, retries, or workarounds
2. Log Analysis
Read ~/.acai/logs/current.log using the Read tool to identify error patterns:
- Filter for error indicators:
Error,Exception,Failed,warn - Cross-reference errors with session tool calls
- Distinguish systemic issues from one-off errors
3. Source File Analysis
Cross-reference findings with source files:
- System prompt:
source/prompts.ts- core prompt components - Tool descriptions:
source/tools/*.ts- each tool has adescriptionstring
Output Format
Present findings as a structured report:
## Session Improvement Analysis
### System Prompt Gaps
- [finding 1]
- [finding 2]
### Tool Description Issues
- [finding 1]
- [finding 2]
### Potential New Tools/Capabilities
- [finding 1]
### Error Patterns (from logs)
- [finding 1]
User Selection
After presenting findings, ask the user to select which improvements to accept:
- Number each finding
- Present as a selection menu
- User responds with numbers (e.g., "1, 3, 5")
Writing Improvements
For accepted findings, write to improvements.md in the project root:
# Improvement Recommendations
## System Prompt
- [accepted finding with context]
## Tool Descriptions
- [accepted finding with specific tool and suggested change]
## New Capabilities
- [accepted finding with rationale]
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.
- 2d ago First seen · 97 lines · 18 tokens per session scan A 0bbb5daaf22e
compounding is a skill published in the GitHub repository travisennis/acai (5 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 551 once invoked, about $0.0001 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 2026-08-31.
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