Defame1297
c048d2320e
Records the upstream agentskills.io sources that informed skill-audit, continuing the research → docs → skill provenance chain. - New references/sources.md with 7 extracted sources attributed to skill files; agentskills-llms-txt demoted to discovery-only comment per skill-author precedent - source_keys frontmatter added to SKILL.md (5 slugs), references/body-discipline.md (agentskills-spec, agentskills-best-practices), and references/description-quality.md (agentskills-spec, agentskills-optimizing-descriptions) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
55 lines
2.6 KiB
Markdown
55 lines
2.6 KiB
Markdown
---
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source_keys:
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- agentskills-spec
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- agentskills-optimizing-descriptions
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---
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# Description Quality Reference
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Source: agentskills.io — optimizing-descriptions
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## How triggering works
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At startup, agents load only the `name` and `description` of each skill. When a user's task matches a description, the agent reads the full `SKILL.md` into context. **The description carries the entire triggering burden** — the body is never seen until after triggering.
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Agents typically consult skills only for tasks requiring knowledge beyond their defaults. Specialized knowledge — unfamiliar APIs, domain-specific workflows, uncommon formats — is where description wording makes the difference.
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## What a good description does
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- **Imperative phrasing** — "Use when..." not "This skill does...". The agent is deciding whether to act.
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- **User intent, not mechanics** — describe what the user is trying to achieve, not how the skill works internally.
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- **Err toward being pushy** — explicitly name contexts where the skill applies, including cases where the user doesn't name the domain: "even if they don't mention X explicitly."
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- **Specificity over vagueness** — "parses and validates OpenAPI specs" beats "helps with APIs."
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- **Near-miss exclusions** — add "Do not use when..." only if a near-miss skill exists that could steal activations. Use strong near-misses (queries that share keywords but need something different), not weak ones ("write a fibonacci function").
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- **Hard limit: 1024 characters** — descriptions grow during revision; check length before finalising.
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## Before / after
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```yaml
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# Weak
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description: Process CSV files.
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# Strong
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description: >
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Analyze CSV and tabular data files — compute summary statistics,
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add derived columns, generate charts, and clean messy data. Use when
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the user has a CSV, TSV, or Excel file and wants to explore, transform,
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or visualize the data, even if they don't explicitly mention "CSV" or
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"analysis."
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```
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The strong version names capabilities precisely and broadens applicability beyond explicit keyword matches.
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## Auditing guidance
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Flag as FAIL if:
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- Phrasing is descriptive ("This skill...") not imperative ("Use when...")
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- Capabilities are vague ("helps with APIs") — require precise verbs and nouns
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- No indirect trigger coverage when indirect cases clearly exist
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- No near-miss exclusions when a sibling skill could plausibly steal activations
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- Length exceeds 1024 characters
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Flag as SUGGESTION if:
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- Indirect trigger coverage exists but could be more specific
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- Near-miss exclusions are present but target weak near-misses only
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