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agent-config

agent-config

github.com/light-chengAgent workflows522 installsUpdated 4d ago
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About agent-config

agent-config plans an execution topology, model tier, and effort for coding-agent work using verified host capabilities and user-confirmed profiles. It supports several named harnesses and uses a generic fallback for others.

Key features

  1. 01Topology and model routing
  2. 02Host capability inspection
  3. 03Task shape and difficulty assessment
  4. 04Setup and profile configuration
  5. 05Approval-gated host changes

Use cases

  1. 01Planning complex multi-agent work
  2. 02Configuring host models and tiers
  3. 03Routing a bounded task by difficulty

MCP support

An optional companion MCP provides setup status, confirmed profile evidence, and configuration tools. Without it, session input or plan-only operation may be used.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/light-cheng/skills --skill agent-config

After installing, type/agent-configin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
companion-contract.md
examples.md
harness-support.md
host-evidence-schema.md
plan-schema.md
profile-schema.md
provider-adapter-contract.md
routing.md
setup.md
task-assessment.md
scripts/
__init__.py
abstract_profiler.py
agent_config_models.py
agent_config.py
candidate_selector.py
decision_source.py
harness_adapter.py
tests/fixtures/
adapter-scenarios.json
case-a-tiered-single-pass.json
case-b-tiered-decomposed.json
case-c-fixed-single-pass.json
case-d-fixed-decomposed.json
execution-config-case-a.json
execution-config-case-b.json
execution-config-case-c.json
execution-config-case-d.json
false-inventory.json
missing-model-evidence.json
missing-reasoning-control.json

Details

From the project README

Agent Config

agent-config maps verified Agent Host capabilities and user-confirmed profile tiers to a right-sized execution topology, model, and effort. It provides native support for primary coding-agent harnesses (Codex, Claude Code, Antigravity, DSH, OpenCode, ZCode, Cursor, Grok Build, Hermes, Pi) with safe generic/manual fallback for others. It has no required companion capability, no external Skill, and no external service requirements.

When to use

  • Before complex multi-agent or partitioned work where topology, model tier, or effort matters.
  • Explicit setup intent (agent-config setup) to configure or reconfigure host models and tiers.
  • When invoked or offered by light-implement or ask-light.

Inputs

  • Bounded task, SPEC, or ticket graph.
  • Evidenced host capabilities and confirmed profile (via companion MCP or session input).

The script entry scripts/agent_config.py takes canonical Host and Profile evidence; missing, stale or mismatched evidence returns NEED_INPUT. Flags and rules: host-evidence-schema.md.

Setup Gate

  • Explicit setup: If invoked with setup intent (agent-config setup), run setup mode to prepare or repair the runtime environment and Profile (see references/setup.md). Setup never plans execution for the current task.
  • Normal invocation: agent-config is the only mode that plans execution topology and routing for current work. Check setup status via companion get_setup_status; health rules are in companion-contract.md. If companion is missing/stale, offer setup or continue plan-only. If Profile is missing or stale, offer setup or continue session-local where safely possible. Never silently enter setup, auto-install MCP tools, or mutate host files.

Output Contract: AgentConfigResult

agent-config yields a canonical AgentConfigResult envelope:

  • readiness: READY | NEED_INPUT | NEED_PROJECT_TICKETS | BLOCKED | UNSUPPORTED (authoritative execution-readiness; redundant status removed).
  • mode: persisted | session-local | plan-only
  • setup_state: companion (ready | missing | stale), profile (persisted | session-local | missing).
  • handoff: "project-tickets" | "setup" | "light-implement" | null
  • execution_config: ExecutionConfig | null (strictly present when readiness === "READY"; strictly null for all non-ready states).

Core flow

  1. Setup check: Verify a confirmed profile via a healthy companion or session input. Never guess single-model without a profile.
  2. Inspect host: Read active models, supported effort values, and concurrency limits.
  3. Determine task shape: Classify as single-pass or decomposed (never by word count).
  4. Decomposition gate: If decomposed and formal tickets do not exist, emit readiness: NEED_PROJECT_TICKETS, handoff: "project-tickets", execution_config: null, and return the ticketing recommendation to the caller.
  5. Difficulty & tier: For multi-model, map work difficulty (routine..critical) to user-confirmed profile tiers (routine, standard, high, review). When the difficulty or reasoning need is not stated, the script may ask a typed decision source (see Optional capabilities).
  6. Resolve effort: Resolve abstract policies (e.g. highest-supported) strictly to verified host-supported strings (e.g. high), never emitting unverified literal max.
  7. Select execution mode:
    • Case A (Fixed Single-model + Single-pass): Direct execution in main session, single model, resolved effort, no fake roles.
    • Case B (Fixed Single-model + Decomposed, P0): Controller main session coordinates fresh worker contexts, same model, actual effort.
    • Case C (Tiered Multi-model + Single-pass): User-configured tier mapped from task difficulty, minimal topology.
    • Case D (Tiered Multi-model + Decomposed, P0): Ticket difficulty mapped to user profile tiers, resolved effort, Controller integration.
  8. Emit plan & apply: Output plan conforming to references/plan-schema.md and AgentConfigResult. Host config mutations require preview approval (preview_configuration → user approval → apply_configuration → validate_configuration).

Invariants

  • No intelligence guessing: Never infer model strength from names or metadata; model tiers are strictly user-confirmed.
  • Single-model is first-class: Single-model is a peer topology, not a degraded fallback. Case B and Case D are both P0 paths.
  • No silent mutation: No automatic package installations, background daemons, or host file edits without explicit consent.
  • Anti-wordcount rule: Semantic complexity and dependencies determine task shape, never prose length.

Handoff

  • Return AgentConfigResult to the caller; handoff names a recommendation, not permission to start another Skill.
  • An already active light-implement caller may resume its authorized bounded item when readiness === "READY".
  • For standalone invocation, recommend explicit $light-implement when ready or $project-tickets when tickets are needed, then stop. Starting either user-invoked stage requires explicit user approval for that exact target and verified host transition support; otherwise show its exact invocation.
  • Code review converges via review-loop; final acceptance belongs to project-review.

Optional capabilities

  • Complexity or reasoning need is not stated → the task profiler asks through the light-decide script path; when you judge without the script, call light-decide with question ids agent-config/task-complexity or agent-config/reasoning-need. It asks only within the project's Decision data: limit (no line means on-device), applies an answer only when the user's policy file calibrates that question, and applies a downgrade only when the score sits clearly inside the lower bin. Unavailable or uncalibrated → keep the deterministic profile. A judgment never confirms a Profile or changes Host configuration.

References

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