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 skills add ai-ecoverse/slicc --skill delegationgit clone --depth 1 https://github.com/ai-ecoverse/sliccWrote 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/ai-ecoverse/slicc/delegation)<a href="https://agentmods.dev/skills/ai-ecoverse/slicc/delegation"><img src="https://agentmods.dev/badge/skills/ai-ecoverse/slicc/delegation.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 findings, up to high
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 →
- high Excessive Agency · line 108 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
- medium Prompt Injection · line 43 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Agent Snooping · line 111 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.
- medium Agent Snooping · line 111 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.
- medium Prompt Injection · line 119 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Agent Snooping · line 298 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 | $0.00101 | $0.05770 |
| Opus 5 | $0.00051 | $0.02885 |
| Sonnet 5 | $0.00020 | $0.01154 |
| Haiku 4.5 | $0.00010 | $0.00577 |
Grade A, and why
delegation scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
agent "$TMPDIR" "curl,jq" "Fetch https://$url/api, return the top-level title field." >> "$TMPDIR/titles.txt" & How it starts
The opening of the file, as written. The whole thing — 341 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delegation
Scoops do the heavy lifting; the cone orchestrates and synthesizes. This skill is about choosing how to delegate, not about administering scoops.
When to delegate
Default to delegation. Parallel scoops almost always finish faster, and the cone's job is synthesis.
Delegate when:
- Multiple independent sources (scraping 3 sites = 3 scoops).
- Time-consuming work that doesn't need direct oversight.
- Work expressible as a clear, self-contained brief.
Do it yourself when:
- Single quick lookup (one page, one API call).
- Real-time adaptation needed (navigating broken URLs).
- Overhead of spawning exceeds benefit.
Brief for authority, not for execution
The most common delegation failure is the cone doing too much pre-work before delegating. The cone researches the topic, makes the design decisions, picks the approach, and then hands the scoop a pre-cooked plan to type out. This is bad on three axes:
- Pollutes the scoop's context. The brief is bloated with conclusions the scoop now has to re-derive an opinion on, instead of facts it can act on.
- Strips the scoop of autonomy. A scoop that's been told what to think can't push back on a bad call or notice a better path mid-task. You get a typist, not a collaborator.
- Wastes the cone's tokens. The cone's strength is orchestration — picking the right scoops, synthesizing their outputs. Doing the research itself burns the cone's context on work that's parallelizable.
Heuristic: if the cone reads files, runs commands, or makes decisions before delegating, that should have been part of the scoop's brief. Hand the scoop the question, the constraints, and the access — let it decide.
| Bad (cone over-prepares) | Good (scoop decides) |
|---|---|
| Cone reads 5 files, picks an approach, tells scoop "implement approach X in file Y." | Scoop is told "the user wants Z; the relevant code is under /workspace/src/. Pick an approach and implement it." |
| Cone scrapes 3 docs, summarizes, then asks scoop to "write a comparison based on this summary." | Scoop is told "compare libraries A, B, C for this use case. Their docs are at . Decide and write the comparison." |
| Cone debugs a failure, isolates the bug, then asks scoop to "fix the off-by-one in line 42." | Scoop is told "this command fails with <output>. Find and fix the bug." (Even better: a one-shot agent for cheap, deterministic bug-fixes.) |
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 · 341 lines · 101 tokens per session scan A 4b2695190888
delegation is a skill published in the GitHub repository ai-ecoverse/slicc (30 stars, last pushed today), licensed Apache-2.0. It adds 101 tokens to every session and 5,770 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
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