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msitarzewski/agency-agents

Scanned commit 053ddbbf39 dated 2026-09-21 — last upstream commit. Generated by codevetter 1.12.0 on 2026-09-22.

github.com/msitarzewski/agency-agents ↗ · 362 files · 4.5 MB

🎭 The Agency: AI Specialists Ready to Transform Your Workflow A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy injectors to reality checkers.

Deep analysis by cli:grok via the grok CLI on 2026-09-22 (344s) — every claim below links to its cited source files.

Overview

The Agency is a MIT-licensed catalog of 279 Markdown agent personalities plus the bash/Python toolchain that converts and installs them into 16 coding-agent hosts. It is aimed at people who want specialized, opinionated prompts (engineering, marketing, security, GIS, and the rest) inside Claude Code, Cursor, Codex, Gemini, Copilot, Hermes, and similar tools, rather than a running application. What is distinctive is the dual catalog: divisions.json and tools.json are enforced as single sources of truth, converters are deterministic, and Hermes gets one lazy-router plugin instead of hundreds of always-loaded skills.

System map

The repo is a content catalog plus a local installer, not a service. Agent source lives in 18 division directories declared by divisions.json. scripts/convert.sh renders tool-specific files under integrations/ (gitignored except READMEs); scripts/install.sh copies or symlinks them into host config directories. Shared parsing and the installer TUI live in scripts/lib.sh. There is no package manifest, database, or HTTP server. A separate desktop app (agency-agents-app) is documented as a consumer of the same catalogs. CI is six GitHub Actions workflows on ubuntu-latest, with the installer also matrixed onto macos-latest.

Feature catalog

User-facing surface is the agent roster, the installer CLI, the converter, NEXUS orchestration docs, and a handful of optional integrations (MCP memory, Chinese Copilot name localization). Agents are activated by pasting or installing their markdown into a host tool, not by an in-repo UI. The installer can target one tool, a division, a slug list, or an agents file, and can dry-run. Hermes exposes four router tools instead of one skill per agent.

All 14 feature catalog claims →

Data flow

Source of truth is the division markdown files. lib.sh parses frontmatter and body. convert.sh transforms each agent into a host format under integrations/, except Claude Code and Copilot, which install the source file unchanged. install.sh filters by slug, then copies or symlinks into a host directory resolved from --path, an env override, or a hardcoded default. Hermes is the outlier: bodies are packed into data/agents.json and only the matched specialist is returned or delegated at runtime. Runbook deploys use a different identifier, the filename stem, than the installer slug.

All 13 data flow claims →

Behavior traces

Three flows dominate: installing into a host, regenerating integration files, and turning the roster into a Hermes plugin that can search and delegate. A fourth, docs-only flow is NEXUS activation by pasting a prompt. The traces below name the functions in call order as they appear in the scripts.

Testing signals

Tests are shell scripts and one unittest module, not a pytest or npm suite. They are designed for bash 3.2 and no jq. CI runs installer behavior on Linux and macOS, catalog consistency on every PR, and agent lint only when agent or linter paths change. The generated-output eval needs PyYAML and Python 3.11 tomllib and treats manifest drift as advisory on pull requests. Large gaps are the converter installers other than the two identity tools, and the agent prompt bodies themselves, which no test executes.

Risk map

The highest-impact code is install.sh, because it writes outside the repo, rewrites Hermes config, can delete a plugin directory, and can symlink the catalog into a host. Agent markdown is prompt supply chain: a merged file is copied verbatim into users' coding agents. The two slug systems and the hardcoded AGENT_DIRS copies are the main ways a catalog change silently drops or mis-addresses agents. Tests pin the identity installers well and the other hosts mostly by conversion invariants.

All 14 risk map claims →

Extension points

New behavior is meant to plug in at three registries: a division, a tool, or a runbook. Agents themselves are just new markdown files that survive lint. Host-specific rendering is a convert_<tool> function plus an install_<tool> function, keyed by tools.json. Hermes tools are registered in one Python register() function inside the generator, not discovered from disk. Color names are a closed case list inside resolve_opencode_color.

Contributor handoff

Read the two catalogs and the three scripts before editing anything. Keep bash 3.2 and no jq. Do not hand-edit generated integration trees. Treat filename stems and frontmatter slugs as different IDs. Run the small shell checks that match the surface you touched; the full convert-output hash only needs --update when a generator changes, and pull-request CI will not fail an agent PR for drift. The dangerous directory is the user's home, not the repo.

All 13 contributor handoff claims →

Languages

LanguageFilesShare of source
Markdown325docs/config
Shell1478%
YAML9docs/config
JSON4docs/config
Python422%

Start reading here

Probable source entrypoint: engineering/ — inferred from the directory tree and manifest, not the upstream docs.

Source roots

engineering/ (64 files) specialized/ (59 files) marketing/ (36 files)

Source layout — engineering/

PathFiles
engineering/engineering-ai-data-remediation-engineer.md1
engineering/engineering-ai-engineer.md1
engineering/engineering-api-platform-engineer.md1
engineering/engineering-ats-validator-architect.md1
engineering/engineering-autonomous-optimization-architect.md1
engineering/engineering-backend-architect.md1
engineering/engineering-china-network-engineer.md1
engineering/engineering-cms-developer.md1
engineering/engineering-code-reviewer.md1
engineering/engineering-codebase-onboarding-engineer.md1
engineering/engineering-data-engineer.md1
engineering/engineering-data-visualization-engineer.md1
engineering/engineering-database-optimizer.md1
engineering/engineering-database-reliability-engineer.md1

Repository structure

Top-level pathFiles
engineering/64
specialized/59
marketing/36
scripts/22
game-development/21
integrations/19
strategy/17
gis/13

Docs found: CONTRIBUTING.mdREADME.md

CI & config entrypoints

Structural health signals

Average score 7/10 across 4 analyzed source files; 1 hotspot surfaced.

These are deterministic review leads — size, churn, and structural signals — not proof of a bug in this project.

Recent history