Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AnastasiyaW/codex-claude-code-config --skill control-cligit clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-configWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/anastasiyaw/codex-claude-code-config/control-cli)<a href="https://agentmods.dev/skills/anastasiyaw/codex-claude-code-config/control-cli"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/control-cli/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/anastasiyaw/codex-claude-code-config/control-cli"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/control-cli.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00068 | $0.00735 |
| Opus 5.5 | $0.00027 | $0.00294 |
| Sonnet 5.5 | $0.00014 | $0.00147 |
| Haiku 4.5 | $0.00007 | $0.00073 |
Grade A, and why
control-cli scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Control CLI
Exercise an interactive terminal program through a small, repeatable harness. Prefer a repository-native demo or test harness; only assemble a temporary PTY or terminal session when the project has no suitable one.
Harness Loop
- Identify the command, smallest fixture, expected ready marker, and cleanup condition.
- Discover existing package scripts, PTY helpers, expect scripts, demo recorders, or TUI tests.
- Launch in an isolated environment with deterministic variables and local disposable data.
- Capture the initial screen or transcript.
- Send one action at a time and wait for a concrete prompt or screen marker.
- Capture the resulting transcript and any requested profile artifact.
- Stop the process and remove temporary sessions, ports, and profiles.
On Windows, prefer the project's own test runner or a checked-in Python/Node
probe. Use ConPTY or an already-installed PTY helper when available; do not add
a dependency just to run a one-off probe. On other systems, tmux, pty, or a
repository-supported terminal harness may be appropriate.
Evidence
For a bug fix or regression, run the same deterministic interaction against the
baseline and treatment and pass the captures to verify-this. For a hang, keep
the last screen, process exit state, timeout, and a stack/CPU sample when
available. For memory growth, use equal repetitions and record before/after
snapshots or a bounded allocation metric.
Prefer stable text markers and accessibility-aware terminal probes over sleeps. If a sleep is unavoidable, state why and keep it bounded.
Safety
- Never send credentials, destructive commands, or production paths into the controlled session.
- Do not rely on stale screen state after navigation, resize, or a prompt change.
- Do not hard-code paths, ports, or commands from another repository.
- Keep transcripts and profiles private when they contain prompts, source, or user data.
Gotchas
- A process that exits successfully before receiving input is not proof that the interactive flow works; assert the ready marker and the expected state change.
- Fixed sleeps hide race conditions and make a green run non-repeatable.
- A terminal transcript can miss rendering defects; use a real UI surface for graphical claims.
- Cleanup must be verified, especially after a timeout or forced interrupt.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 72 lines · 68 tokens per session scan A c97b5f0ceca6
control-cli is a skill published in the GitHub repository AnastasiyaW/codex-claude-code-config (212 stars, last pushed yesterday), licensed MIT. It adds 68 tokens to every session and 735 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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