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 olddonkey/olddonkey-skills --skill engineering-modegit clone --depth 1 https://github.com/olddonkey/olddonkey-skillsWrote 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/olddonkey/olddonkey-skills/engineering-mode)<a href="https://agentmods.dev/skills/olddonkey/olddonkey-skills/engineering-mode"><img src="https://agentmods.dev/badge/skills/olddonkey/olddonkey-skills/engineering-mode.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 5.1 | $0.00101 | $0.01614 |
| Opus 5 | $0.00051 | $0.00807 |
| Sonnet 5 | $0.00020 | $0.00323 |
| Haiku 4.5 | $0.00010 | $0.00161 |
Grade A, and why
engineering-mode 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 6d 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.
This is a copy
94% identical to cursor-engineering-mode — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engineering mode
Own the outcome; delegate every code change. Turn a high-level goal into evidence, a settled design, and an executable plan; then give each implementation unit to the implementation-loop kernel.
Routing precedence
Evaluate these rules strictly in order. Stop at the first decisive route.
- Explicit invocation wins, always. An explicitly invoked skill owns the request. Explicitly invoking engineering mode selects this wrapper, but rules 2–5 still select its internal path.
- Plan-only or no-implementation instructions stop implementation. Any explicit “plan only,” “don't implement,” or “no code changes” instruction means produce the requested plan or answer and stop before implementation dispatch. Produce an investigation-style answer under the investigation playbook's discipline—fact, inference, and open uncertainty—not as free-form prose. A direct prohibition on code changes dominates every shortcut below.
- Fast-path only an explicitly requested code change. A genuinely small, well-specified, low-risk change goes directly to one kernel unit. Merely mentioning code is not a change request: fall through to rule 5. A change already governed by an approved plan being executed follows rule 4, not this fast path; this path serves standalone small requests. Check it before playbook selection, so smallness trumps category. Record verification under the verification contract. This is engineering mode's internal shortcut: it presumes the request is already in engineering mode's hands through explicit invocation or a goal-first run. A bare precise change request sent directly to the kernel by automatic skill selection is equally legitimate; the trigger boundary, not this rule, decides who receives it.
- Pass approved plans through without redesign. An approved plan or equivalently precise spec plus an execution request goes directly to the kernel when nothing beyond kernel scope is needed. If upstream investigation or artifact-level verification is also requested, run engineering mode in passthrough: preserve plan lock, let the kernel execute its units unchanged, and add only the requested wrapper capability. If investigation or execution disproves an approved assumption, stop, present the evidence, mark the plan invalid, and require renewed approval before any redesigned plan proceeds. Plan lock forbids silent drift, not honest invalidation.
- Choose a playbook by evidence. Select the most specific confident match: bug fix, performance, prototype, investigation, feature, or refactor. Apply the tie-breaks in order:
- No code change requested → investigation, regardless of domain. A performance question is investigation.
- Measured improvement is the deliverable → performance.
- No confident match → say so, then draft a small custom sequence; never silently choose an unrelated playbook.
What ships with it
11 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.
- references/adapter.md 1.3 KB
- references/handoff.md 2.1 KB
- references/playbooks/bug-fix.md 1.2 KB
- references/playbooks/feature.md 1.1 KB
- references/playbooks/investigation.md 1.5 KB
- references/playbooks/performance.md 2.4 KB
- references/playbooks/prototype.md 1.3 KB
- references/playbooks/refactor.md 1.2 KB
- references/verification-contract.md 4.9 KB
- scripts/tree-oid-selftest.sh 30 KB runs code
- scripts/tree-oid.sh 13 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.
- 6d ago First seen · 74 lines · 101 tokens per session scan A ea1ac6966271
engineering-mode is a skill published in the GitHub repository olddonkey/olddonkey-skills (16 stars, last pushed 18d ago), licensed MIT. It adds 101 tokens to every session and 1,614 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to cursor-engineering-mode, differing in 10 lines, and is treated as a copy.
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