majiayu000
majiayu000/claude-skill-registry
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/majiayu000/claude-skill-registry --skill inject명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
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SKILL.md 표시 중
| name | inject |
| description | Load relevant .agents context. |
| practices | ["wiki-knowledge-surface","pragmatic-programmer"] |
| hexagonal_role | driving-adapter |
| consumes | [] |
| produces | [] |
| context_rel | [] |
| skill_api_version | 1 |
| user-invocable | false |
| context | {"window":"fork","intent":{"mode":"none"},"sections":{"exclude":["TASK"]},"intel_scope":"full"} |
| metadata | {"tier":"background","dependencies":[],"internal":true} |
| output_contract | stdout: injected knowledge summary |
DEPRECATED (removal target: v3.0.0) — Use
ao lookup --query "topic"for on-demand learnings retrieval and phase-scoped context packets. This skill and theao injectCLI command still work as compatibility adapters, but they are not the canonical context path and are not called from default hooks or other skills.
On-demand knowledge retrieval. Not run automatically at startup (since ag-8km).
It is read-only: it only reads knowledge for injection and never writes to .agents/.
Load relevant prior knowledge into the current session as a legacy adapter.
| Field | Value |
|---|---|
| Lease | retire-candidate |
| Replacement port | retrieve_context / assemble_context |
| Replacement adapters | ao lookup, knowledge brief artifacts |
| Current allowed use | manual compatibility lookup only |
| Not allowed | default startup injection, hidden hook delivery, task planning |
In the default manual startup mode, MEMORY.md is auto-loaded by Claude Code and no startup injection occurs. Prefer ao lookup for on-demand retrieval and bounded per-phase packets. Use /inject or ao inject only for legacy compatibility.
In lean or legacy startup modes (set via AGENTOPS_STARTUP_CONTEXT_MODE), the SessionStart hook runs:
# lean mode (MEMORY.md fresh): 400 tokens
ao inject --apply-decay --format markdown --max-tokens 400 \
[--bead <bead-id>] [--predecessor <handoff-path>]
# legacy mode: 800 tokens
ao inject --apply-decay --format markdown --max-tokens 800 \
[--bead <bead-id>] [--predecessor <handoff-path>]
This legacy path searches for relevant knowledge and prints a bounded summary.
When --bead is provided (via HOOK_BEAD env var from Gas Town):
When --predecessor is provided (path to a handoff file):
Given /inject [topic]:
With ao CLI:
ao lookup --query "<topic>" --limit 5
Without ao CLI, search manually:
# Global operating memory
sed -n '1,120p' ~/.agents/MEMORY.md 2>/dev/null
# Recent learnings
ls -lt .agents/learnings/ | head -5
# Recent patterns
ls -lt .agents/patterns/ | head -5
# Recent research
ls -lt .agents/research/ | head -5
# Global learnings (cross-repo knowledge)
ls -lt ~/.agents/learnings/ 2>/dev/null | head -5
# Global patterns (cross-repo patterns)
ls -lt ~/.agents/patterns/ 2>/dev/null | head -5
# Legacy patterns (read-only fallback, no new writes)
ls -lt ~/.claude/patterns/ 2>/dev/null | head -5
Use the Read tool to load the most relevant artifacts based on topic.
Present the injected knowledge:
After presenting injected knowledge, record which files were injected for the feedback loop:
mkdir -p .agents/ao
# Record each injected learning file as a citation
for injected_file in <list of files that were read and presented>; do
echo "{\"artifact_path\": \"$injected_file\", \"cited_at\": \"$(date -Iseconds)\", \"session_id\": \"$(date +%Y-%m-%d)\", \"workspace_path\": \"$PWD\"}" >> .agents/ao/citations.jsonl
done
Citation tracking enables the feedback loop: learnings that are frequently cited get confidence boosts during /post-mortem, while uncited learnings decay faster.
| Source | Location | Priority | Weight |
|---|---|---|---|
| Global Memory | ~/.agents/MEMORY.md | Highest | 1.0 |
| Learnings | .agents/learnings/ | High | 1.0 |
| Patterns | .agents/patterns/ | High | 1.0 |
| Global Learnings | ~/.agents/learnings/ | High | 0.8 (configurable) |
| Global Patterns | ~/.agents/patterns/ | High | 0.8 (configurable) |
| Research | .agents/research/ | Medium | — |
| Retros | .agents/learnings/ | Medium | — |
| Legacy Patterns | ~/.claude/patterns/ | Low | 0.6 (read-only, no new writes) |
Knowledge relevance decays over time (~17%/week). More recent learnings are weighted higher.
Hook triggers: session-start.sh runs at session start with AGENTOPS_STARTUP_CONTEXT_MODE=lean or legacy
What happens:
ao inject --apply-decay --format markdown --max-tokens 400 (lean) or --max-tokens 800 (legacy).agents/learnings/, .agents/patterns/, .agents/research/ for relevant artifactsResult: Prior learnings, patterns, and research are available for legacy hook profiles. This is not the default AgentOps 3.0 path.
Note: In the default manual mode, MEMORY.md is auto-loaded by Claude Code and this hook emits only a pointer to on-demand retrieval commands (ao search, ao lookup).
User says: /inject authentication or "recall knowledge about auth"
What happens:
ao lookup --query "authentication" --limit 5Result: Topic-specific knowledge retrieved and summarized, enabling faster context loading than full artifact reads.
| 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 |
ao inject CLI command behavior (header, JSON contract, --for filtering), linked to cmd tests (soc-jnfgi)SOC 직업 분류 기준