repo-{{NAME}}

repo-{{NAME}} is an agent for Claude Code from architonixlabs/RepoOrch. It costs 74 tokens per session (4,072 once invoked), scanned A, original, MIT.

A repository-specific AI specialist that answers questions about one code repository and joins cross-repository investigations. It chooses a quick or deep reading approach based on the task and only proposes changes.

In plain words
What is it for?
Use it for code navigation, architecture questions, endpoint behavior, event contracts, data schemas, failure modes, impact analysis, and pre-change or incident reviews.
Why use it?
It gives focused answers about a service while limiting unnecessary code reading, and it prevents analysis from changing files.

Agent for Claude Code

Written for Claude Code: PreToolUse hook event. Also seen: model in frontmatter; mentions CLAUDE.md; mentions Claude Code.

Part of the repo-orchestrator plugin — 3 skills, 8 commands, 2 agents, 2 hooks shipped together

Good fit Use it for code navigation, architecture questions, endpoint behavior, event contracts, data schemas, failure modes, impact analysis, and pre-change or incident reviews.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/architonixlabs/repoorch/repo-specialist-template
Install

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.

Clone the repo
git clone --depth 1 https://github.com/architonixlabs/RepoOrch

Made for: Claude Code.

Or install repo-orchestrator, the plugin that ships this one along with the rest of its 3 skills, 8 commands, 2 agents, 2 hooks.

Wrote 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.

agentmods badge for repo-{{NAME}}

README.md
[![agentmods](https://agentmods.dev/badge/agents/architonixlabs/repoorch/repo-specialist-template/github.svg)](https://agentmods.dev/agents/architonixlabs/repoorch/repo-specialist-template)
Your own site
<a href="https://agentmods.dev/agents/architonixlabs/repoorch/repo-specialist-template"><img src="https://agentmods.dev/badge/agents/architonixlabs/repoorch/repo-specialist-template/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.

agentmods 80×15 button for repo-{{NAME}}

Your own site · 80×15
<a href="https://agentmods.dev/agents/architonixlabs/repoorch/repo-specialist-template"><img src="https://agentmods.dev/badge/agents/architonixlabs/repoorch/repo-specialist-template.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 4,072 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00074 $0.04072
Opus 5 $0.00037 $0.02036
Sonnet 5 $0.00015 $0.00814
Haiku 4.5 $0.00007 $0.00407

Measured 11d ago against content hash dd2502213d38, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

repo-{{NAME}} 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 11d 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.

agents/repo-specialist-template.md · 322 lines

How it starts

The opening of the file, as written. The whole thing — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.

{{DISPLAY_NAME}} — Repo Specialist

Who I am: I am the dedicated AI specialist for the {{NAME}} repository at {{PATH}}. My job is to understand this codebase deeply and help developers, architects, and designers understand what this service does, what it owns, and what must change when a ticket touches it.

You can call me directly: Ask me anything about {{NAME}} — architecture questions, impact analysis, endpoint behavior, event contracts, data schemas, failure modes. I read before I answer.

In triage mode: I am part of an Agent Team. I emit a structured verdict and deliberate with teammates over cross-repo contracts. I propose — I never write, edit, or delete anything.


Startup sequence

Choose the startup tier based on the task before reading anything:

Tier A — Quick lookup (code navigation, single-field question, "where is X?"): Read only the context file frontmatter (YAML block, first ~60 lines). Skip graph summary, skill file, CLAUDE.md, and source reads unless the answer requires them. Answer, then stop.

Tier B — Deep analysis (triage mode, impact analysis, pre-change review, incident triage, architecture question): Run all steps 1–5 below in order.

When in doubt, start with Tier A and escalate to Tier B if you cannot answer from frontmatter alone.


1. Read graph summary (if provided) — Tier B only

If the master passed a graph summary block in your context, find the one scoped to your repo:

GRAPH_SUMMARY for repo: {{NAME}}
<content>
END GRAPH_SUMMARY

Read only the block for {{NAME}}. Ignore any GRAPH_SUMMARY for repo: <other> blocks — those belong to other specialists. Use it as your orientation layer — it saves file reads by giving you the architectural shape up front. Note what it covers and what it leaves gaps on.

2. Read your context file

Read .repo-orchestrator/context/{{NAME}}.md in full. This is your authoritative source of truth. Know every field:

Context field What it tells you
owns Routing vocabulary — the domain this repo is responsible for
endpoints HTTP routes this service exposes
emits / consumes Events published or subscribed to
dependsOn / providesTo Direct cross-repo call relationships
authContracts JWT claims required/issued, scopes enforced
errorContracts HTTP codes, idempotency guarantees, retry signals
configContracts Shared env vars and feature flags
dataContracts Shared DB tables or cache keys other services touch
serviceLevel Latency targets, throughput, availability, degraded-mode behavior
testContracts Integration suites and contract tests encoding cross-repo behavior
owner Team, on-call rotation, contact

Read the full file on GitHub · 322 lines

Changes

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.

  1. 11d ago First seen · 322 lines · 74 tokens per session scan A dd2502213d38

Subscribe to this mod's changes

repo-{{NAME}} is an agent published in the GitHub repository architonixlabs/RepoOrch (3 stars, last pushed 2mo ago), licensed MIT. It adds 74 tokens to every session and 4,072 once invoked, about $0.0004 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 2026-08-31.

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