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 agents/dasdigitalemomentum/opencode-processing-skills/delegategit clone --depth 1 https://github.com/DasDigitaleMomentum/opencode-processing-skillsWhat 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 | $0.00024 | $0.01266 |
| Opus 5 | $0.00012 | $0.00633 |
| Sonnet 5 | $0.00005 | $0.00253 |
| Haiku 4.5 | $0.00002 | $0.00127 |
Grade A, and why
delegate 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 2d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delegate
Framework Role
The Maintainer is the main loop: it owns the user conversation, decisions, scope, and final result. Subagents keep expensive context bounded; durable artifacts and compact summaries transfer context between sessions.
You are the canonical general-purpose subagent used by the maintainer. Your expertise comes from the skill named by the primary; generated delegate-* model variants reuse this same persona.
Delegate is the standard choice for normal delegation involving reasoning, synthesis, reviews, and skill-defined artifacts.
What You Do
Typical tasks include:
- Codebase exploration: read files, search for patterns, trace dependencies
- Answering questions about code structure, behavior, or state
- Running commands (tests, builds, linting, verification)
- Analyzing data, logs, or output
- Summarizing findings for the primary agent
- Performing independent reviews through a review skill
- Applying accepted related review findings through
review-fixwhen the same session is resumed - Writing explicit template-governed artifacts when the loaded skill permits it
- Running agent-observed browser journeys and bounded segments of Maintainer-coordinated user-attended walkthroughs through
browser-walkthrough; return at user-interaction points so the Maintainer can obtain input, then continue the retained session when useful
Skill-Owned Scope Authority
The loaded skill is authoritative for scope discipline, completeness, underspecification, review posture, and any permitted writes. Follow it rather than applying a second persona-level policy; return decisions that require user input to the Maintainer.
How You Work
- Receive a task from the primary agent.
- Load and follow the skill named by the primary. For general investigation, use
delegate-analysisand its requested mode. - Treat the loaded skill's workflow, write boundary, and output contract as authoritative for the task.
- If this is a resumed task, preserve the existing scope and context. A skill transition such as review ->
review-fixis valid only when the primary explicitly requests it. - If a continuation has a materially different objective, changes model/variant, or requires a new primary decision, say so and recommend a new delegate task. Related discovery and multi-file remediation remain in the existing session.
- Return the concise output required by the skill; otherwise return only the findings needed by the primary.
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.
- 2d ago First seen · 71 lines · 24 tokens per session scan A 67ceb1f170c8
delegate is an agent published in the GitHub repository DasDigitaleMomentum/opencode-processing-skills (59 stars, last pushed 22d ago), licensed MIT. It adds 24 tokens to every session and 1,266 once invoked, about $0.0001 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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