Borrowing it
Nothing to install: this file belongs to mazumba/opencode-dockerized. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/mazumba/opencode-dockerized/main/.opencode/config/skills/deepwork/SKILL.mdgit clone --depth 1 https://github.com/mazumba/opencode-dockerizedWrote 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/mazumba/opencode-dockerized/deepwork)<a href="https://agentmods.dev/skills/mazumba/opencode-dockerized/deepwork"><img src="https://agentmods.dev/badge/skills/mazumba/opencode-dockerized/deepwork/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/mazumba/opencode-dockerized/deepwork"><img src="https://agentmods.dev/badge/skills/mazumba/opencode-dockerized/deepwork.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00038 | $0.00964 |
| Opus 5.5 | $0.00015 | $0.00386 |
| Sonnet 5.5 | $0.00008 | $0.00193 |
| Haiku 4.5 | $0.00004 | $0.00096 |
Grade A, and why
deepwork 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deepwork
Deepwork is an orchestrator workflow for heavy coding sessions. Use it when the work is broad, risky, multi-file, or likely to span several implementation phases. Do not use it for trivial edits, quick docs changes, or simple bug fixes.
Core Contract
When deepwork is active, the orchestrator must manage the work as a scheduler, not as the default implementation worker.
Required behavior:
- keep OpenCode todos aligned with the active deepwork phase;
- create and maintain a local markdown progress file under
.slim/deepwork/; - write valuable research findings into that file as confirmed research context when they are received and reconciled;
- draft a plan before implementation;
- ask
@oracleto review the plan and revise it until acceptable; - create a phased implementation/delegation plan;
- before oracle reviews, add relevant confirmed research findings and file references to the deepwork file so oracle can review the plan or phase from accepted context instead of redoing discovery;
- ask
@oracleto review that implementation plan before execution; - after oracle review and before each implementation phase, decide the execution path: what can run in parallel, what must be sequential, which specialists to delegate to, and whether to split the same agent into multiple bounded lanes;
- after each phase, validate, update the deepwork file, prepare the plan file
for oracle review and ask
@oracleto review the phase result, fix actionable issues, then continue; - when a phase includes
@designer, preserve designer intent across later phases. Use@fixeronly for mechanical follow-up that does not alter the UI/UX; - finish with final validation and a concise summary.
Designer Handoff Guardrail
When a deepwork phase includes @designer, treat the delivered UI/UX as
accepted design intent for later phases. Record any important design decisions in
the deepwork file before continuing.
After designer work:
- preserve layout, rhythm, hierarchy, motion, spacing, color, affordances, responsiveness, and component feel;
- review and improve user-facing copy with grounded, normal wording, but do not change visual structure or interaction intent;
- route follow-up visual, responsive, motion, hierarchy, polish, or
component-feel changes back to
@designer; - use
@fixeronly for bounded mechanical follow-up that preserves the design exactly, such as wiring, tests, type fixes, or non-visual behavior changes; - if design intent must change, record why in the deepwork file before changing it.
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 · 112 lines · 38 tokens per session scan A 14c91ef8dca4
deepwork is a skill published in the GitHub repository mazumba/opencode-dockerized (6 stars, last pushed 2d ago), licensed MIT. It adds 38 tokens to every session and 964 once invoked, about $0.0002 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 2026-08-31.
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