Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts
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Analyze external URL to evaluate fit with oh-my-customcode project and auto-create GitHub issue with verdict
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설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Analyze an external URL (tech blog, tool, library, methodology) to evaluate its fit with the oh-my-customcode project and auto-create a GitHub issue with a structured verdict.
/scout <url>
/scout https://news.hada.io/topic?id=27673
/scout https://github.com/user/repo
| Verdict | Meaning | Label | Follow-up |
|---|---|---|---|
| INTERNALIZE | Aligns with project philosophy; should become a skill/agent/guide | scout:internalize + P1/P2/P3 | /research or direct implementation |
| INTEGRATE | Useful but best kept as external dependency | scout:integrate + P2/P3 | Plugin/MCP integration review |
| SKIP | Irrelevant or duplicates existing functionality | scout:skip | Issue created then closed |
Before any work, validate the URL:
# Check URL is syntactically valid
echo "$URL" | grep -qE '^https?://'
If invalid: [Pre-flight] GATE: Invalid or unreachable URL. Please check and retry. — abort.
Search existing GitHub issues for prior scout reports on the same URL domain:
DOMAIN=$(echo "$URL" | sed 's|https\?://||' | cut -d'/' -f1)
gh issue list --state all --label "scout:internalize,scout:integrate,scout:skip" \
--json number,title,body --jq ".[] | select(.body | contains(\"$DOMAIN\"))" 2>/dev/null
If found: [Pre-flight] WARN: Similar URL already scouted in issue #N. Proceed anyway? [Y/n]
Before execution, show the plan:
[Scout] {url}
├── Phase 1: Fetch & Summarize
├── Phase 2: Load Project Philosophy
├── Phase 3: Fit Analysis (sonnet)
└── Phase 4: Issue Creation
Estimated: ~1 min | Cost: ~$0.5-1.5
Execute? [Y/n]
WebFetch(url) — retrieve page contentRead(CLAUDE.md) — extract architecture philosophy:
Read(README.md) — extract project overview and component inventoryGlob(.claude/skills/*/SKILL.md) — list existing skills for overlap detectionSpawn 1 sonnet agent with the following analysis prompt.
Inputs:
Analysis dimensions:
| Dimension | Question |
|---|---|
| Philosophy alignment | Does it match the compilation metaphor, separation of concerns, "create experts on demand"? |
| Technical fit | Does it complement or overlap with existing skills/agents/guides? |
| Integration effort | How much work to internalize vs. use externally? |
| Value proposition | What concrete benefit does it bring to the project? |
Agent prompt template:
You are a project fit analyst. Given:
1. External content summary:
{phase1_summary}
2. Project philosophy:
{phase2_philosophy}
3. Existing skills ({skill_count} total):
{skill_list}
Analyze the external content against the project philosophy across 4 dimensions:
- Philosophy alignment
- Technical fit (overlap with existing skills?)
- Integration effort (XS/S/M/L)
- Value proposition
Return a structured verdict:
- verdict: INTERNALIZE | INTEGRATE | SKIP
- priority: P1 | P2 | P3
- rationale: 2-3 sentences
- philosophy_table: criterion/fit/rationale for each dimension
- recommendation: specific integration plan or skip reason
- next_steps: 2-3 actionable items
- escalation: true/false (INTERNALIZE + M/L effort = true)
Output: Structured verdict with rationale.
gh label create "scout:internalize" --color "0E8A16" --description "Scout: should be internalized" 2>/dev/null || true
gh label create "scout:integrate" --color "1D76DB" --description "Scout: keep as external" 2>/dev/null || true
gh label create "scout:skip" --color "D4C5F9" --description "Scout: skip" 2>/dev/null || true
gh issue create \
--title "[scout:{verdict}] {content_title}" \
--label "scout:{verdict},P{n}" \
--body "{issue_body}"
SKIP: auto-close the issue:gh issue close {number} -c "Auto-closed: scout verdict is SKIP"
## Scout Report: {title}
**Source**: {url}
**Verdict**: {INTERNALIZE / INTEGRATE / SKIP}
**Priority**: {P1 / P2 / P3}
## Summary
{2-3 sentence summary of the external content}
## Philosophy Alignment
| Criterion | Fit | Rationale |
|-----------|-----|-----------|
| Compilation metaphor | {check/cross} | {explanation} |
| Separation of concerns (R006) | {check/cross} | {explanation} |
| Dynamic agent creation | {check/cross} | {explanation} |
| Existing skill overlap | {check/cross} | {overlapping skills list} |
## Recommendation
{Specific integration plan — which skill/agent/guide to create, or why to skip}
## Next Steps
- [ ] {follow-up action 1}
- [ ] {follow-up action 2}
---
Generated by `/scout`
When verdict is INTERNALIZE and integration effort is M or L:
[Advisory] Deep analysis recommended.
└── Consider running: /research {url}
[Scout Complete] {title}
├── Verdict: {INTERNALIZE / INTEGRATE / SKIP}
├── Priority: {P1 / P2 / P3}
├── Issue: #{number}
└── Escalation: {/research recommended | none}
| Phase | Model | Rationale |
|---|---|---|
| Phase 1 (Fetch) | orchestrator | Simple WebFetch, no agent needed |
| Phase 2 (Load) | orchestrator | Simple Read/Glob, no agent needed |
| Phase 3 (Analysis) | sonnet | Balanced reasoning for fit analysis |
| Phase 4 (Issue) | orchestrator | gh issue create via Bash |
| Rule | How |
|---|---|
| R009 | Single agent in Phase 3 — no parallelism needed |
| R010 | Orchestrator manages phases 1/2/4; analysis delegated to sonnet agent in Phase 3 |
| R015 | Display scout plan before execution (Display Format section) |
| Scenario | Better Alternative |
|---|---|
| Deep multi-source research | /research <url> |
| Internal project analysis | /omcustom:analysis |
| Known tool evaluation | Direct agent conversation |
| Bulk URL analysis (5+) | /research with URL list |
| Aspect | /scout | /research |
|---|---|---|
| Purpose | Quick fit evaluation | Deep multi-dimensional analysis |
| Teams | 1 agent | 10 teams |
| Cost | ~$0.5-1.5 | ~$8-15 |
| Duration | 1-2 min | 10-20 min |
| Output | Issue with verdict | Full report with ADOPT/ADAPT/AVOID |
| When | First contact with new link | Deep dive after scout recommends |
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Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts
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Auto-detect project context and optimize harness — deactivate unused agents/skills, suggest missing experts, generate project profile
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Adversarial code review using attacker mindset — trust boundary, attack surface, business logic, and defense evaluation
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Apache Airflow best practices for DAG authoring, testing, and production deployment
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Alembic migration patterns for naming conventions, safety checks, expand-contract, env.py configuration, and CI integration
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Pre-routing ambiguity analysis — scores request clarity and asks clarifying questions when needed (inspired by ouroboros)
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