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/mifunedev/openharness/delegatenpx skills add mifunedev/openharness --skill delegategit clone --depth 1 https://github.com/mifunedev/openharnessWhat 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 | $0.00067 | $0.02993 |
| Opus 5 | $0.00034 | $0.01496 |
| Sonnet 5 | $0.00013 | $0.00599 |
| Haiku 4.5 | $0.00007 | $0.00299 |
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 — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delegate
Parallel execution coordinator. Read a plan or conversation context, decompose it into a dependency-ordered task graph, and spawn worker sub-agents in parallel waves. Each wave completes before the next begins. Results are collected, validated, and reported.
Core principle: maximize parallelism while respecting dependencies absolutely.
Worker model and thinking policy
Apply this policy to every worker:
- Inherit the parent/session model by default. Omit the Agent tool's
modelargument. Do not route routine or simple work to a weaker model tier. - Set the Agent tool's
thinkingparameter from task complexity: simple/mechanical →low, standard →medium, complex →high, and architecture or debugging with substantial uncertainty →xhigh. Supported levels areoff,minimal,low,medium,high, andxhigh; never usemax. - If the selected thinking level is unsupported by the inherited model/provider, use the nearest supported level. Do not switch models merely to obtain a thinking level.
- Override
modelonly with an explicit task-specific reason: an operator request, an unavailable required capability/context, a strict latency or budget constraint, or local benchmark evidence. Record that reason in the task graph and pass the override only for that worker.
Decision Flow
flowchart TD
A["Resolve input: $ARGUMENTS or conversation context"] --> B{Plan found?}
B -->|No| FAIL["Report: no plan found"]
FAIL --> MEM_FAIL[Memory Protocol]
B -->|Yes| C["Step 2: Deep-think task decomposition"]
C --> D["Step 3: Build dependency graph"]
D --> E["Step 4: Create tasks + compute waves"]
E --> F{--dry-run?}
F -->|Yes| DRY["Report: task graph + wave plan"]
DRY --> MEM_DRY[Memory Protocol]
F -->|No| G["Step 5: Execute Wave N"]
G --> G1["Worker A"]
G --> G2["Worker B"]
G --> G3["Worker C"]
G1 & G2 & G3 --> H{All passed?}
H -->|No| I["Mark dependents BLOCKED, continue independent"]
I --> J{More waves?}
H -->|Yes| J
J -->|Yes| G
J -->|No| K["Step 6: Validate"]
K --> L["Step 7: Report"]
L --> MEM_OP[Memory Protocol]
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 · 266 lines · 67 tokens per session scan A a6c952464278
delegate is a skill published in the GitHub repository mifunedev/openharness (36 stars, last pushed 2d ago), licensed Apache-2.0. It adds 67 tokens to every session and 2,993 once invoked, about $0.0003 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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