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/hmbown/codewhale/delegatenpx skills add Hmbown/CodeWhale --skill delegategit clone --depth 1 https://github.com/Hmbown/CodeWhaleWhat 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 | $0.00036 | $0.00663 |
| Opus 5 | $0.00018 | $0.00331 |
| Sonnet 5 | $0.00007 | $0.00133 |
| Haiku 4.5 | $0.00004 | $0.00066 |
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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delegate
Use sub-agents when they can do focused work in parallel while the parent keeps architectural judgment, integration, and final verification.
Keep vs Delegate
Keep in the parent:
- Understanding the user's actual request and constraints
- Architecture, security, product, and release-risk decisions
- Cross-module integration
- Final review, test interpretation, and user-facing summary
Delegate to sub-agents:
- Read-only exploration over a bounded file set
- Mechanical edits with a clear file ownership boundary
- Focused test or lint runs
- Boilerplate generation from an explicit spec
- Independent checks that can run while parent work continues
Do not delegate tiny one-step tasks, ambiguous product decisions, destructive operations without a clear acceptance criterion, or final verification.
Launch Focused Work
Use agent for a focused child run. Launch independent children together so they can run in parallel.
Prefer provider-neutral model_strength over hardcoded model ids. Children inherit the active model by default (model_strength: "same"), including type: "scout", so pass model_strength: "faster" explicitly to get the cheaper same-family sibling for read-only exploration:
{
"name": "config_audit",
"prompt": "Inspect crates/tui/src/config.rs and crates/tui/src/settings.rs for duplicate model-default logic. Return file/line findings only; do not edit files.",
"type": "scout",
"model_strength": "faster",
"cwd": "."
}
For code changes, give the child a precise write boundary and tell it not to revert unrelated edits. Keep implementation children capable with model_strength: "same":
{
"name": "docs_patch",
"prompt": "Update only docs/configuration.md to document the new [statusline] keys. Match the surrounding style. Do not edit other files.",
"type": "builder",
"model_strength": "same",
"cwd": "."
}
Use fork_context: true only when the child genuinely needs the current conversation prefix. Leave it omitted for fresh, narrower context.
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 · 91 lines · 36 tokens per session scan A c9cd48fbc33d
delegate is a skill published in the GitHub repository Hmbown/CodeWhale (40,889 stars, last pushed today), licensed MIT. It adds 36 tokens to every session and 663 once invoked, about $0.0002 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.
Other skills, from other repositories
work
Execute spec.json (plan mode) or review.findings.json (fix-findings mode) by dispatching subagents per chunk. Triggers on "work on", "implement", "execute plan", "carry on", "continue".
write-zot-extension
Help the user create a new zot extension (slash command, LLM tool, or guard) in any language.
flywheel-conventions
Shared conventions for Flywheel subagents. Tool discipline, output format, research patterns.
yolo
Autonomously execute the full plan → implement → review → fix cycle without stopping. The agent makes every decision, including answering open questions during plan-consolidation. Use when you'll be away from the keyboard and trust the agent to ship.
model-audit
Compare the unified models registry (per-mode model IDs, contexts, effort lists, and defaults) against what the providers actually ship today: codex app-server model/list, claude --help --effort, and the Anthropic/OpenAI docs. Reports delisted models, mode/effort drift, and duplicate mappings. Read-only — proposes a…
subagent-harness-mcp-control
Static Phase 0a marker skill used only to observe plugin visibility.