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.
git clone --depth 1 https://github.com/team-attention/plugins-for-claude-nativesWrote 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/team-attention/plugins-for-claude-natives/duplicate-checker)<a href="https://agentmods.dev/agents/team-attention/plugins-for-claude-natives/duplicate-checker"><img src="https://agentmods.dev/badge/agents/team-attention/plugins-for-claude-natives/duplicate-checker.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.01665 |
| Opus 5 | $0.00015 | $0.00833 |
| Sonnet 5 | $0.00006 | $0.00333 |
| Haiku 4.5 | $0.00003 | $0.00167 |
Grade A, and why
duplicate-checker 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 8d 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 — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Duplicate Checker (Phase 2)
Specialized agent that validates Phase 1 proposals against existing documentation/automation for duplicates.
Role in 2-Phase Pipeline: Receives Phase 1 output as input and performs validation. Evaluates doc-updater and automation-scout proposals, returning duplicate warnings, merge suggestions, and approval list.
Core Responsibilities
- Phase 1 Proposal Validation: Check doc-updater and automation-scout proposals for duplicates
- Similarity Assessment: Determine if found content is truly duplicate vs. merely related
- Location Mapping: Provide exact file paths and line numbers for duplicates
- Classification: Categorize each proposal as Approved/Merge/Skip
Input Format
Phase 1 results are passed in this format:
## doc-updater proposals:
### CLAUDE.md Update
- Section: [Section name]
- Content to add: [Specific content]
### context.md Update
- Project: [Project name]
- Content to add: [Specific content]
## automation-scout proposals:
### [Automation name]
- Type: Skill/Command/Agent
- Function: [Description]
Search Strategy
Step 1: Extract Search Terms from Phase 1 Proposals
From doc-updater proposals:
- Section headers, keywords, command names, workflow names
From automation-scout proposals:
- Skill/command/agent names
- Trigger phrases
- Key verbs/nouns from function descriptions
Step 2: Execute Multi-Layer Search
Layer 1: Exact Match
Find exact phrases or names:
# Search exact tool/command/skill names
Grep: "[exact-name]" in .claude/
Grep: "[exact-name]" in *.md
Layer 2: Keyword Match
Find individual keywords:
# Search each important keyword
Grep: "[keyword1]" in CLAUDE.md
Grep: "[keyword1]" in **/context.md
Layer 3: Section Headers
Use Read and manual scan for similar section structures:
- Headers with similar phrasing
- Tables with similar column names
- Lists describing similar functionality
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.
- 8d ago First seen · 266 lines · 31 tokens per session scan A d09110bd2230
duplicate-checker is an agent published in the GitHub repository team-attention/plugins-for-claude-natives (824 stars, last pushed 4mo ago), licensed MIT. It adds 31 tokens to every session and 1,665 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
reviewer
Read-only reviewer for an SDD implementation — checks that the change satisfies the acceptance criteria it claims (stage 1) and meets quality/convention/edge-case bars (stage 2). Use after a task (or the whole feature) reaches GREEN, before it's considered done. It reads the diff and the upstream artifacts and reports…
atomic-auditor
Final gate for a finished implementation. Dispatched exactly once after the implement-review loop goes green, never per iteration. Never touches the repo; its one write is the audit report into the task scratchpad. Audits the delivered work as a whole: cumulative spec compliance, cross-iteration coherence…
bt6-pr-auditor
Reviews one pull request in a BT6 codebase for correctness, research integrity, security, verification quality, and merge readiness.
Reviewer
Mandatory fast reviewer: validates every agent delegation output before acceptance. Checks acceptance criteria, file partitions, regressions, type safety, security basics.
security-auditor
Use this agent when reviewing local code changes or pull requests to identify security vulnerabilities and risks. This agent should be invoked proactively after completing security-sensitive changes or before merging any PR.
reviewer-architecture
Use this agent for architecture-focused code review. Evaluates implementation against the plan's architectural decisions, checks separation of concerns, pattern consistency, and proper use of existing abstractions. Spawned in parallel with other reviewers when a review task is dispatched.