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Agentit

CI Status License: Apache-2.0 Release

Agentit is a portable, provider-neutral meta-harness for AI coding agents: activate with natural language, interview once, load only the skill family you need, spawn specialists when useful, critique large plans, verify with evidence, and ship through PRs.

Agentit is designed to work across OpenAI, Anthropic, Google, xAI, and compatible future coding-agent environments. Provider-specific subagents/workers are optional execution primitives; the shared Agentit protocol is semantic and portable.

Use it

The only special phrase is a natural use Agentit in your language:

usa agentit
use agentit
utilise agentit

No other powerwords. Ordinary prompts drive routing (“frontend and backend”, two file paths, “at the same time”, “review and fix”, “several agents”, …).

usa agentit y crea mi portfolio personal

For product-affecting work Agentit follows roughly:

inspect facts
   ↓
one comprehensive interview batch
   ↓
domain pack (+ craft depth only if design/visual)
   ↓
project-aware token estimate
   ↓
persist resumable project state
   ↓
skill budget + MCP fit + optional specialists
   ↓
critic on large structural plans
   ↓
implement on work branch
   ↓
verification → PR by default

Purely mechanical chores can bypass the interview.


Interview-first, domain packs, design craft only

Agentit interviews every product-affecting task, not only ambiguous ones.

Before asking, the agent inspects repo/docs/tools. Then it asks all currently identifiable material decisions in one batch.

It recommends a domain pack (skill family: frontend, backend, design, data, …) and loads only that family plus a tiny always-core, not the whole catalog.

Standard / Polished / Studio are design/visual craft depth only — not a universal tax on every task. Token estimates are project-aware (router token_estimate), not fixed billing tables.

Canonical files: skills/interview-me/SKILL.md, effort/levels.yaml, docs/AGENTIT_INTERVIEW_AND_PROVIDER_POLICY.md, skills/mcp-tooling-fit/SKILL.md.


Continuity: sessions are disposable

Agentit assumes any chat can disappear because of context/token exhaustion, provider/model switch, app crash, machine switch, or a long pause.

For every product-affecting task, maintain a compact project state document at:

docs/agentit/STATE.md

If the project already has an equivalent canonical state file, reuse it instead.

The state must let a completely fresh agent recover:

  • what is being built and why;
  • confirmed intent, audience, success criteria, constraints, and non-goals;
  • domain pack, craft depth if design/visual, spend, token estimate;
  • what is done / in progress / blocked / not started;
  • durable product, architecture, API, data, and design decisions;
  • important files/artifacts;
  • branch + PR;
  • verification commands/results;
  • next executable actions;
  • open user questions/blockers.

Update it after interview confirmation, expensive-to-rediscover decisions, meaningful milestones, before handoff/context exhaustion/pause, and before completion.

Do not persist secrets, credentials, raw chain-of-thought, full chat transcripts, or giant tool dumps.

Canonical policy: docs/PROJECT_CONTINUITY.md.


Git: branch + PR by default

For repository changes Agentit defaults to:

work branch → commits → verification → pull request → review/user merge decision

It should not commit/fast-forward directly onto main/master and should not auto-merge PRs unless the user explicitly authorizes that exception for the task or project instructions require another workflow.

Continuity/docs updates travel in the same branch/PR as implementation.


Provider-neutral specialist layer

agents/catalog.yaml defines semantic roles with small skill bundles and output contracts. Examples include:

frontend-developer
backend-architect
ai-engineer
devops-automator
design-system-researcher
ui-researcher
trend-researcher
creative-tool-scout
visual-storytelling-director
spatial-experience-designer
delight-and-whimsy
design-critic
performance-benchmarker
api-tester
workflow-optimizer

Agentit uses intelligent delegation: stay single-agent when that is best; spawn specialists when independence, isolation, domain expertise, or independent critique wins. No hard min/max subagent caps. Large structural plans require an independent critic. If the user asks for multi-agent without benefit, the Architect should push back.

Execution fallback:

native provider subagent/worker
        ↓ unavailable
isolated delegated model/tool call
        ↓ unavailable
separate fresh-context invocation
        ↓ unavailable
parent + exact specialist skill bundle

Multi-agent execution is an optimization, never a correctness dependency.


Provider-neutral capability resolution

Specialists declare stable required and preferred capability IDs such as repository.read, design.inspect, or browser.inspect. Agentit resolves those IDs against an explicit host inventory using ordered ChatGPT app, MCP, CLI, and local fallbacks.

specialist -> capabilities -> explicit available providers -> scoped grants

No inventory means no assumed grant. Delegated workers receive only the selected capability/provider permissions, and an explicit unresolved required capability fails the pre-spawn gate. Resolution is plan-only: Agentit does not install, authenticate, enable, or call providers.

./agentit capabilities resolve \
  --specialist frontend-developer \
  --host codex \
  --available mcp.github,local.filesystem,mcp.playwright

See docs/CAPABILITIES.md for the catalog, inventory contract, fallbacks, least-privilege envelope, and extension guide.


UI/UX Pro Max intelligence

Agentit's design profile includes ui-ux-pro-max-intelligence, a provider-neutral JIT adapter for the MIT-licensed upstream nextlevelbuilder/ui-ux-pro-max-skill.

The upstream project provides searchable product-aware intelligence for style families, palettes, typography, UX/accessibility rules, icons, charts, GSAP/motion patterns, landing structures, and many implementation stacks.

Agentit deliberately treats it as an intelligence source, not the creative director:

UI UX Pro Max lookup
       ↓
compact product/design baseline
       ↓
Taste / creative direction / research
       ↓
implementation
       ↓
Impeccable / Emil / critic

The database should be queried JIT. Do not dump it wholesale into model context and do not let a preset style automatically become the art direction.

Effort behavior:

  • Standard: narrow lookup only when it prevents a mistake or answers a concrete design question.
  • Polished: targeted product/style/color/type/UX intelligence when useful.
  • Studio: one evidence source among live inspiration research, concept exploration, creative direction, and independent critique.

See skills/ui-ux-pro-max-intelligence/SKILL.md and THIRD_PARTY_NOTICES.md.


Design studio

The design profile contains a broad but JIT-routed craft stack:

ui-ux-pro-max-intelligence       structured UI/UX design intelligence
design-inspiration-research      live project-specific references
design-trend-researcher          emerging / maturing / saturated patterns
creative-web-experiences         concept generation
design-taste-frontend            art direction / visual thesis
impeccable-design                critique / polish / responsive craft
emil-design-eng                  interaction and motion feel
visual-storytelling-director     narrative beats and pacing
creative-tool-scout              current implementation tooling
figma-design-workflow            official Figma MCP workflow
scrollytelling-web               narrative scroll architecture
gsap-scrolltrigger               pin/scrub/timeline mechanics
gsap-performance                 motion runtime performance
threejs-spatial-experiences      rooms/stores/museums/worlds
threejs-product-storytelling     GLB/glTF product storytelling
delight-and-whimsy               restrained memorable details

Do not load the whole stack just because design is active. Effort level and task signals control depth.

For genuinely high-ambition Studio work, Agentit may use a design competition: shared evidence brief → 2-3 independent concepts → explicit jury by brand fit/originality/clarity/usability/feasibility/performance/memorability → winner or justified hybrid → implementation → independent critique.


Profiles

profiles.yaml keeps the global install bounded and activates deeper capabilities JIT.

Profile Purpose
core bounded everyday engineering harness
frontend browser/performance/UI maintenance
design full craft studio + UI/UX intelligence
backend API/service/observability
supabase Postgres/Supabase guidance
product discovery/spec/marketing
writing documentation/writing
release CI/migration/launch
research context/spec/adversarial review
all escape hatch only
agentit enable design --project . --apply
agentit status --project .
agentit disable design --project . --apply

Verification

Agentit separates model claims from verification evidence.

agentit verify "task summary" --project .
agentit verify "task summary" --project . --apply

No done, fixed, or passing claim without fresh evidence after the last relevant edit. Design work needs rendered evidence when browser tooling is available; high-ambition work should normally get independent critique/performance review.


MCP runtime

agentit mcp status
agentit mcp enable context7 --apply
agentit mcp enable-stack developer_core --apply
agentit mcp enable-stack design_studio --apply

The design studio stack can combine Figma, Context7, Playwright, and Chrome DevTools. MCPs are optional capabilities, not portability requirements.


Install

git clone https://github.com/marcmarti9/agentit.git ~/code/agentit
cd ~/code/agentit
bash install.sh --provider all --with-guides --apply
ln -sf ~/code/agentit/agentit ~/.local/bin/agentit

Open Skills / compatible clients typically use ~/.agents/skills/; Claude can use ~/.claude/skills/; Codex can use ~/.codex/skills/. Shared Agentit semantics remain provider-neutral.


Testing

python3 -m unittest discover -s router -p "test_*.py"
python3 -m unittest discover -s tests
python3 evals/run.py

Docs map

Doc Purpose
AGENTS.md global agent playbook
docs/AGENTIT_INTERVIEW_AND_PROVIDER_POLICY.md batched interview + effort + provider semantics
docs/PROJECT_CONTINUITY.md resumable project-state contract + PR-first workflow
agents/catalog.yaml reusable specialist roles
effort/levels.yaml Standard / Polished / Studio budgets
docs/MCP_CATALOG.md MCP catalog/runtime
docs/ADAPTIVE_AGENT_ARCHITECTURE.md orchestration topologies/contracts
THIRD_PARTY_NOTICES.md upstream design-skill attribution

License

Licensed under the Apache License, Version 2.0. Third-party adaptations/integrations retain their applicable notices in THIRD_PARTY_NOTICES.md.

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Portable, provider-neutral harness for safe AI coding-agent orchestration, skill routing, and configuration management.

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