inject
Inject Skill
Typically runs automatically via SessionStart hook.
Inject relevant prior knowledge into the current session.
How It Works
The SessionStart hook runs:
ao inject --apply-decay --format markdown --max-tokens 1000
This searches for relevant knowledge and injects it into context.
Manual Execution
Given /inject [topic]:
Step 1: Search for Relevant Knowledge
With ao CLI:
ao inject --context "<topic>" --format markdown --max-tokens 1000
Without ao CLI, search manually:
# Recent learnings
ls -lt .agents/learnings/ | head -5
# Recent patterns
ls -lt .agents/patterns/ | head -5
# Recent research
ls -lt .agents/research/ | head -5
Step 2: Read Relevant Files
Use the Read tool to load the most relevant artifacts based on topic.
Step 3: Summarize for Context
Present the injected knowledge:
- Key learnings relevant to current work
- Patterns that may apply
- Recent research on related topics
Knowledge Sources
| Source | Location | Priority |
|---|---|---|
| Learnings | .agents/learnings/ |
High |
| Patterns | .agents/patterns/ |
High |
| Research | .agents/research/ |
Medium |
| Retros | .agents/retros/ |
Medium |
Decay Model
Knowledge relevance decays over time (~17%/week). More recent learnings are weighted higher.
Key Rules
- Runs automatically - usually via hook
- Context-aware - filters by current directory/topic
- Token-budgeted - respects max-tokens limit
- Recency-weighted - newer knowledge prioritized
Examples
SessionStart Hook Invocation
Hook triggers: session-start.sh runs at session start
What happens:
- Hook calls
ao inject --apply-decay --format markdown --max-tokens 1000 - CLI searches
.agents/learnings/,.agents/patterns/,.agents/research/for relevant artifacts - CLI applies recency-weighted decay (~17%/week) to rank results
- CLI outputs top-ranked knowledge as markdown within token budget
- Agent presents injected knowledge in session context
Result: Prior learnings, patterns, research automatically available at session start without manual lookup.
Manual Context Injection
User says: /inject authentication or "recall knowledge about auth"
What happens:
- Agent calls
ao inject --context "authentication" --format markdown --max-tokens 1000 - CLI filters artifacts by topic relevance
- Agent reads top-ranked learnings and patterns
- Agent summarizes injected knowledge for current work
- Agent references artifact paths for deeper exploration
Result: Topic-specific knowledge retrieved and summarized, enabling faster context loading than full artifact reads.
Troubleshooting
| Problem | Cause | Solution |
|---|---|---|
| No knowledge injected | Empty knowledge pools or ao CLI unavailable | Run /post-mortem to seed pools; verify ao CLI installed |
| Irrelevant knowledge | Topic mismatch or stale artifacts dominate | Use --context "<topic>" to filter; prune stale artifacts |
| Token budget exceeded | Too many high-relevance artifacts | Reduce --max-tokens or increase topic specificity |
| Decay too aggressive | Recent learnings not prioritized | Check artifact modification times; verify --apply-decay flag |