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knowledge-base-for-startups

AWS Startups reference content — Activate FAQ, credits guide, programs, partner offers, sample architectures, and hundreds of learn articles spanning generative AI, cloud architecture, cost optimization, security, fundraising, go-to-market, and real-world startup case studies. Use when the user asks factual questions about AWS Activate (eligibility, credits, programs, providers), wants a sample architecture or solution guide, or needs an AWS-curated learn article on a specific startup topic. For copy-paste AI prompts (RAG chatbot, MVP scaffold, security baseline, GPU quota, etc.), see the prompt-library-for-startups skill. Do not use for: account-specific lookups (credits balance, Activate membership status, application status), real-time event listings beyond the events stub, or content not present in the bundled `references/` tree.

Quality

92%

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SKILL.md
Quality
Evals
Security

Quality

Content

92%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-engineered reference-skill body: index-first progressive disclosure, concrete MUST rules, literal response phrasings for gated/stub content, explicit error branches, and a freshness procedure. The only weakness is minor duplication of the events/showcase stub guidance and some overlap between the routing table and the section prose.

Suggestions

Deduplicate the events/showcase stub guidance: state the 'deliberately minimal stubs → hand over live URL' rationale once (Live-URL redirects) and have Scope notes reference it in one line instead of restating it.

Fold the routing-hints table's pointer rows (events, showcase) into a single 'stubs → live URL' row and drop rows that merely restate the Reference pages table, tightening the body without losing navigation.

DimensionReasoningScore

Conciseness

The body is dense and operational (routing table, MUST rules, keyword-filter procedure) with essentially no explanation of concepts Claude already knows. It sits at 'efficient; minor instances of over-explanation that could be trimmed' rather than 5 because the events/showcase stub rationale is stated twice ("Live-URL redirects" section and "Scope notes" — e.g. "The events and showcase pages are deliberately minimal stubs" repeats the earlier "Two pages are deliberately minimal stubs"), and the routing table re-summaries mappings the section prose already covers.

4 / 5

Actionability

Guidance is copy-paste ready for an instruction-only skill: exact file paths ("references/learn.md", "references/faq.md"), a concrete procedure ("filter by keyword first, then open the linked detail file"), literal response phrasings ("respond along the lines of: 'Virtual and in-person AWS Startups events happening around you can be found at https://aws.amazon.com/startups/events.'"), hard rules ("MUST quote verbatim", "MUST cite source_url"), and an exact command ("npx skills update knowledge-base-for-startups"). Specific examples cover the common query cases via the routing table — a clear score-5 match.

5 / 5

Workflow Clarity

The lookup workflow is clearly sequenced: open the index first, "filter by keyword, then open at most one detail file per question", answer with verbatim quote + source_url, then the post-answer freshness check with an explicit condition ("If the gap is more than 6 months"). Error-recovery branches are explicit: "If the index points to a sign-in-gated row, do not attempt to open the detail file — surface the title + Live URL" and "If the topic is not covered, say so plainly rather than improvising". No destructive/batch operations exist, so no validation cap applies; this matches the score-5 anchor rather than score 4's 'minor validation gaps'.

5 / 5

Progressive Disclosure

SKILL.md is a pure routing overview pointing to well-signaled index files (learn.md, offers.md, build.md) which in turn link one level into the detail trees; every referenced path was verified to exist in the bundle (references/learn/<category>/<slug>.md, references/offers/<slug>.md, all reference pages and stubs). Each reference is described with its purpose and navigation pattern ("They have a Keywords column — filter by keyword first"), matching the 'clear overview with well-signaled one-level-deep references; easy navigation' anchor.

5 / 5

Total

19

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: concrete corpus inventory, explicit multi-clause 'Use when' triggers, explicit exclusions, and cross-skill disambiguation, all in third person without padding. The only gap is that a few natural topic terms (showcase, events, contact) are absent from the positive trigger list.

DimensionReasoningScore

Specificity

Quotes like "Activate FAQ, credits guide, programs, partner offers, sample architectures, and hundreds of learn articles spanning generative AI, cloud architecture, cost optimization, security, fundraising, go-to-market, and real-world startup case studies" give a comprehensive, concrete inventory of the corpus, and the use cases ("asks factual questions", "wants a sample architecture or solution guide", "needs an AWS-curated learn article") are concrete actions. Nothing is vague or generic; this matches the 'comprehensive coverage' anchor, not the score-4 anchor which requires minor gaps in coverage.

5 / 5

Completeness

Both 'what' (the full corpus inventory) and 'when' ("Use when the user asks factual questions about AWS Activate (eligibility, credits, programs, providers), wants a sample architecture or solution guide, or needs an AWS-curated learn article on a specific startup topic") are explicitly and concretely stated, with negative scope ("Do not use for: account-specific lookups...") on top. This clearly matches the score-5 anchor, not score 4 where 'when' is present but less explicit.

5 / 5

Trigger Term Quality

Natural trigger terms are strong: "AWS Activate", "eligibility", "credits", "programs", "providers", "sample architecture", "solution guide", plus topic keywords like "cost optimization", "security", "fundraising", "go-to-market". It sits at the 'good keyword coverage; a few natural terms missing' anchor rather than 5 because a few natural user phrases for corpus topics (showcase, events, contacting/support) appear only in the exclusion clause or not at all.

4 / 5

Distinctiveness Conflict Risk

The niche is unambiguous (AWS Startups/AWS Activate reference content) and it actively defuses conflicts with sibling skills ("For copy-paste AI prompts... see the prompt-library-for-startups skill") and account-specific lookups. Minimal conflict risk — a clear match for the score-5 anchor rather than the 'minor overlap risk' of score 4.

5 / 5

Total

19

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 1 suspicious

Warning

referenced_paths_exist

Referenced path issues: 1 missing, 1 deeper-than-1-level

Warning

Total

14

/

16

Passed

Repository

aws/agent-toolkit-for-aws

Path

plugins/aws-startup-advisor/skills/knowledge-base-for-startups/SKILL.md

Reviewed

Table of Contents

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