mcpField
C
cline-runner

cline-runner

github.com/robsonrungAgent workflows240 installsUpdated 1d ago
Repository

About cline-runner

cline-runner runs a scoped prompt through the local authenticated Cline CLI, for workflows that need explicit model selection and verified results. It checks the serving-model receipt and does not allow provider fallback.

Key features

  1. 01Runs prompts through the local Cline CLI
  2. 02Selects provider and model together
  3. 03Supports read-only plan and act modes
  4. 04Checks serving-model receipt and result
  5. 05Supports isolated state for concurrent calls

Use cases

  1. 01Run a scoped task with an approved model
  2. 02Keep analysis in read-only plan mode
  3. 03Verify which model served a request

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/robsonrung/rar-skills --skill cline-runner

After installing, type/cline-runnerin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
cline-lanes.example.json
command-reference.md
continuation.md
runtime-reference.md
scripts/
cline_lanes.py
run_cline.py
tests/
test_cline_lanes.py

Details

From the project README

Cline Runner

Execute the caller's scoped prompt through the local CLI. Shared roles, envelope keys, and result handling live in shared/references/runner-common.md. Preserve seat fidelity: name the provider that actually answered, and report unavailable or unverified seats honestly.

Native routing

Read shared/references/host-model-execution.md before choosing an external route. If the current host can dispatch the exact selected provider model with the required effort, isolation, and receipt policy in a native subagent or task thread, use that route. agents/openai.yaml is host UI metadata; it does not dispatch a native model.

Invocation

Set SKILL_DIR to this loaded skill directory in the same shell call:

SKILL_DIR="<absolute path of this skill directory>";
python3 "$SKILL_DIR/scripts/run_cline.py" "<scoped prompt>" --json

An approved workflow supplies the exact model, effort, role, tool mode, and receipt policy. Pass those approved options and --disable-fallback; this basic example does not authorize a different route.

Runtime boundaries

  • Use the local authenticated cline CLI. Select provider and model together; catalog IDs can differ across providers.
  • Analysis roles default to enforced read-only plan mode with read tools enabled. --no-tools instead rejects all tool calls. Act mode permits writes and auto-approves tools within the caller's authority.
  • Prompt and file context may be sent to the selected provider. --model mutates persisted provider configuration unless state is isolated with --data-dir or an authenticated lane.
  • Concurrent calls require separate authenticated state directories and bounded credential-pool slots. A missing lane must not fall back to shared state.
  • Named Muse and Minimax seats are selected with --seat. The runtime reference records their mappings and the files that must stay in sync.
  • No provider fallback is allowed. The stream's serving-model receipt and terminal result determine the observed model and success.

Load by need

Result

Read agent_message and the wrapper envelope. Check success, serving-model receipt, effective runner/provider, and any fallback or malformed-output status. A completed process alone does not prove the requested task or model was used. Report touched files when the caller authorized edits.

Comments

Markdown supported