AC claude-code-bridge
Bridges OpenClaw (QQ, Telegram, WeChat, and other messaging channels) to a persistent Claude Code CLI session running in a background tmux process. Enables starting, stopping, restarting, and monitoring Claude Code sessions directly from any chat interface. Automatically detects session state on every message, routes user input to the active Claude Code session, and handles tool-approval prompts so the user can approve or deny Claude Code actions without leaving their chat app. Ideal for developers who want to control Claude Code from a mobile device or a group chat. Trigger phrases: "start claude code", "open claude code", "cc status", "stop claude code", "restart cc", "启动claude code", "开启claude code", "连接cc", "cc状态", "关闭cc", "退出cc", "重启cc", "/cc start", "/cc stop", "/cc restart", "/cc status".
As a process C 52/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 52/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 27 mutating operations with no state check
- 40Consistency. Frontmatter name (claude-code-bridge) differs from the folder (cc-bridge)
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 100Steps. 18 steps
- 100Failures and branches. 4 branches, has a failure section
- 100Execution cost. Instruction body is 1248 tokens
- low The response is described with custom markup (3 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 806: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 11 example trigger phrases
- +4Structure: 10 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.