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 agentmods add skills/bahayonghang/my-ai-cli-toolkit/codex-workflow-recommendernpx skills add bahayonghang/my-ai-cli-toolkit --skill codex-workflow-recommendergit clone --depth 1 https://github.com/bahayonghang/my-ai-cli-toolkitWrote 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/bahayonghang/my-ai-cli-toolkit/codex-workflow-recommender)<a href="https://agentmods.dev/skills/bahayonghang/my-ai-cli-toolkit/codex-workflow-recommender"><img src="https://agentmods.dev/badge/skills/bahayonghang/my-ai-cli-toolkit/codex-workflow-recommender.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00097 | $0.00719 |
| Opus 5 | $0.00048 | $0.00360 |
| Sonnet 5 | $0.00019 | $0.00144 |
| Haiku 4.5 | $0.00010 | $0.00072 |
Grade A, and why
codex-workflow-recommender 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 5d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex Workflow Recommender
Read-only: do not create, edit, install, remove, configure, or write externally; reports never authorize implementation.
Workflow
- Confirm outcome, repo root, surface, and scope; read applicable
AGENTS.md/code_map.md. - Inventory relevant gates, roots, trusted config, plugins, and MCP. Prefer
structured tools or
rgand current help. - Summarize minimum fields, never raw doctor/config/auth/provider/env values.
Preserve provenance:
built-in,user-config,project-config,plugin-provided,installed-enabled,installed-disabled,available-uninstalled,unsupported,missing evidence. - Decide whether persistence is justified.
No change recommendedis valid. Smallest owner: one-off -> prompt; repo rule -> AGENTS; learned context -> memory; repeated flow -> skill; team bundle -> plugin; live external need -> MCP; independent role -> subagent; runtime default -> config/rule; lifecycle event -> hook; schedule -> automation. - Reuse suitable native/installed capability first. Technology detection alone is only a signal. Rank by impact, evidence, dependency, effort, reversibility, and Permission/data risk.
- Stop at supported decisions; keep OMX conditional and omit irrelevant surfaces.
Output Contract
Return Outcome; Evidence and Unknowns; supported Prioritized Recommendations;
dependency/risk Implementation Sequence; Verification and Rollback; and
Approval Options split by local versus persistent/external action. Each item:
Observed evidence; Existing capability/provenance; scope; prerequisites;
Permission/data risk; confidence or missing evidence; Verification;
Rollback/defer reason. Omit empty categories.
References
What ships with it
21 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/interface.yaml 917 B
- evals/evals.json 4.6 KB
- evals/output/cases.jsonl 10 KB
- evals/output/fixtures/codex-workflow-scenarios.md 2.0 KB
- manifest.json 1.4 KB
- references/codex-surface-map.md 2.9 KB
- references/hooks-patterns.md 1.6 KB
- references/mcp-servers.md 1.6 KB
- references/plugins-reference.md 1.4 KB
- references/skills-reference.md 1.6 KB
- references/subagent-templates.md 1.5 KB
- reports/output_blind_answer_key.json 1.8 KB
- reports/output_blind_review_pack.json 11 KB
- reports/output_blind_review_pack.md 6.2 KB
- reports/output_quality_scorecard.json 26 KB
- reports/output_quality_scorecard.md 1.3 KB
- reports/output-risk-profile.json 4.5 KB
- reports/output-risk-profile.md 2.7 KB
- reports/prompt-quality-profile.json 5.3 KB
- reports/prompt-quality-profile.md 4.5 KB
- tests/contracts.test.mjs 6.4 KB runs code
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.
- 5d ago First seen · 67 lines · 97 tokens per session scan A 62a89215c8c3
codex-workflow-recommender is a skill published in the GitHub repository bahayonghang/my-ai-cli-toolkit (16 stars, last pushed today), licensed MIT. It adds 97 tokens to every session and 719 once invoked, about $0.0005 per session on Opus 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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