FD codex-tmux
Launch long-running Codex (or Claude Code) coding tasks via tmux on WSL2/Linux, bypassing SIGTERM timeouts. Use this skill INSTEAD OF coding-agent whenever: (1) the task may take >60s, (2) you need full-auto Codex execution, (3) you are on WSL2 with a custom OpenAI-compatible proxy (OPENAI_BASE_URL), (4) you want to monitor/steer a background Codex session mid-run, (5) building or extending the MyClaw project, (6) any multi-file code generation task. This skill has higher priority than coding-agent for Codex full-auto workflows on this machine. Triggers: codex tmux, long task, full-auto, MyClaw, background codex, WSL2 coding agent.
As a process D 46/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
What is at stake
The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.
The files contain someone else's key or token. If it is live, your agent will call third-party services under a stranger's identity; if it was revoked, the skill's scripts simply fail. Such a key often arrives with the author's whole workspace, personal data included.
The key is visible to everyone who downloaded the skill and has likely been copied by catalog-scanning bots already. Revoke it now, check bills and access logs, then reissue.
How to improve
- Remove the critical guard findings (secrets, dangerous commands, hidden instructions): while they stand the skill is blocked and cannot grade above F.
- 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 · 1
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critical Secrets in code
secret-openai-keySKILL.md:19OpenAI-style API key (quoted — discussed, not commanded)OPENAI_API_KEY="sk-5…9Ef"
quoted
Files scanned: 2. 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 46/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (bash, git) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 75Steps. 3 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 507 tokens
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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 639: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 3 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.