Borrowing it
Nothing to install: this file belongs to MercurieVV/ScalaSemantic. 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/MercurieVV/ScalaSemantic/master/.claude/skills/task-splitting-evaluation/SKILL.mdgit clone --depth 1 https://github.com/MercurieVV/ScalaSemanticWrote 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/mercurievv/scalasemantic/task-splitting-evaluation)<a href="https://agentmods.dev/skills/mercurievv/scalasemantic/task-splitting-evaluation"><img src="https://agentmods.dev/badge/skills/mercurievv/scalasemantic/task-splitting-evaluation/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/mercurievv/scalasemantic/task-splitting-evaluation"><img src="https://agentmods.dev/badge/skills/mercurievv/scalasemantic/task-splitting-evaluation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 92 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00073 | $0.01518 |
| Opus 5 | $0.00036 | $0.00759 |
| Sonnet 5 | $0.00015 | $0.00304 |
| Haiku 4.5 | $0.00007 | $0.00152 |
Grade A, and why
task-splitting-evaluation 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 9d 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 — 144 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task Splitting And Evaluation
Use this skill before the implementation-oriented orchestrate skill. This flow does not write code, create branches, or merge PRs. It builds a bounded GitHub issue tree so every executable leaf has a clear task description and selected worker engine/model.
Agents
.claude/agents/task-tree-triage.md- cheap Haiku classifier for one issue. It decides whether to skip, make the issue an executor-ready leaf, or send it to the smart planner for subtask expansion..claude/agents/task-plan-architect.md- strongest-model expansion planner. It inspects one broad issue, creates bounded GitHub subtasks, selects a preferred engine/model for each subtask, and comments the parent with the generated task tree.
Processing Marker
Every processed issue must get exactly one durable marker comment unless it is skipped because an equivalent marker or executor-ready comment already exists:
### Agentic task-tree marker
Status: leaf-ready|expanded|skipped
Processed-by: task-splitting-evaluation-v1
Tree depth: <n>
This marker is the loop guard. Never process an issue twice in the same run, and never process an issue that already has this marker in its body or comments.
Outcomes
For each unprocessed issue, choose exactly one outcome:
-
leaf-ready- Use when the task can be implemented directly by one worker.
- Add a task comment with a detailed implementation-ready description if the issue does not already have one.
- Select the preferred executor engine/model from
.claude/orchestrate-routing.md. - The issue becomes a tree leaf.
-
expanded- Use when the task is broad, vague, risky, or naturally decomposes into dependent steps.
- Run
.claude/agents/task-plan-architect.mdwith the smartest available LLM/model. Do not cost-optimize the planning model for this step. - The architect creates one GitHub issue per subtask and links it to the parent as a native GitHub sub-issue with GraphQL
addSubIssue. - Comment the parent with child issue links, dependency order, and per-child executor/model choices.
- Newly created subtasks enter the queue and are processed by the same rules.
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.
- 9d ago First seen · 144 lines · 73 tokens per session scan A 111ef920d3cf
task-splitting-evaluation is a skill published in the GitHub repository MercurieVV/ScalaSemantic (21 stars, last pushed yesterday), licensed MIT. It adds 73 tokens to every session and 1,518 once invoked, about $0.0004 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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