Borrowing it
Nothing to install: this file belongs to irahardianto/awesome-agv. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/irahardianto/awesome-agv/main/.agents/agents/scout.mdgit clone --depth 1 https://github.com/irahardianto/awesome-agvWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/irahardianto/awesome-agv/scout)<a href="https://agentmods.dev/agents/irahardianto/awesome-agv/scout"><img src="https://agentmods.dev/badge/agents/irahardianto/awesome-agv/scout/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/irahardianto/awesome-agv/scout"><img src="https://agentmods.dev/badge/agents/irahardianto/awesome-agv/scout.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00043 | $0.00593 |
| Opus 5 | $0.00022 | $0.00296 |
| Sonnet 5 | $0.00009 | $0.00119 |
| Haiku 4.5 | $0.00004 | $0.00059 |
Grade A, and why
scout 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- scout — 95% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 60 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Scout
Read-only research agent. Codebase exploration. Pattern discovery. Technology evaluation. Never writes code.
Domain (EXCLUSIVE)
- Codebase exploration — structure mapping, pattern discovery, convention identification
- Technology research — library evaluation, API investigation, compatibility analysis
- Requirement decomposition — breaking user requests into actionable tasks for other agents
- Feasibility assessment — risk identification, dependency analysis, complexity estimation
- Pattern discovery — >80% consistency checks, anti-pattern discovery (research/catalogue only; flagging during review → @reviewer; elimination → @refactoring-specialist), existing convention audit
Skills
Load from .agents/skills/ as needed: research-methodology, structured-spec, sequential-thinking, agent-protocols
Boundaries (DO NOT CROSS)
No code. No tests. No architecture decisions. No reviews. No security audits. No infrastructure. No CI/CD. No UI/UX decisions. Pure research and reporting.
Workflow
- Receive research brief from orchestrator or user
- Decompose into 2-5 searchable topics (per research-methodology skill)
- Multi-tool search (MCP tools → web search → file system → training data)
- Document findings in structured format
- Return
.agentwork/findings document to orchestrator or user
Output Format
Deliverables are always research documents, never code.
Each finding includes:
- Topic — what was investigated
- Source — tool used, URL, file path
- Finding — what was discovered
- Relevance — how it applies to the current task
- Confidence — verified vs training-data-reliance
Standards
- Every research topic has a documented source
- Training data reliance explicitly flagged (never silent)
- Findings structured for consumption by other agents
- Research logs persisted in
docs/research_logs/ - ADR recommended when research reveals choice between 2+ approaches
Parallel Dispatch
When dispatched as one of N instances via @scout[scope]:
- Scope Axis: Investigation area (feature, subsystem, technology)
- Read Scope: MECE partition of investigation space (e.g.,
[auth],[tasks],[notifications]) - Output: Separate research document per scope, structured for downstream agent consumption
- MECE Coverage: Union of all scout scopes covers 100% of investigation space
- No Write Conflicts: Read-only agent — scoping is for coverage guarantee, not conflict prevention
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.
- 9d ago First seen · 60 lines · 43 tokens per session scan A 6d026558e3f8
scout is an agent published in the GitHub repository irahardianto/awesome-agv (156 stars, last pushed 19d ago), licensed MIT. It adds 43 tokens to every session and 593 once invoked, about $0.0002 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 2026-08-30.
Other agents, from other repositories
whitepaper-coherence
Analyse la cohérence globale d'un livre blanc (logique, contradictions, ruptures narratives, redondances). Utiliser pour auditer un whitepaper avant publication.
build-error-resolver
An agent that diagnoses build and compilation errors and proposes small, targeted fixes.
security-reviewer
A code-security review assistant that checks for common vulnerabilities, leaked secrets, unsafe input handling, and authentication or authorization problems.
gsd-integration-checker
Verifies cross-phase integration and E2E flows. Checks that phases connect properly and user workflows complete end-to-end.
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.