BC Long Context RAG Analyzer
AI-powered long-context document analysis and RAG optimization assistant — process 100K-2M token documents, build hybrid search indexes, evaluate retrieval quality, handle multi-document reasoning, and generate structured reports. Built for financial analysts, legal professionals, researchers, and developers working with large-scale document datasets. Keywords: long context, RAG, retrieval augmented generation, document analysis, vector search, hybrid search, chunking strategy, context window, financial report analysis, legal document review, research paper synthesis, 长上下文, Gemini 2M token, 文档理解, 向量检索, 混合检索, RAG优化, 知识库.
As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 1
✓ No critical or high findings
Medium and low: 1
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low Secrets in code
secret-high-entropy-tokenSKILL.md:312High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)- Language: Chinese optimized (use 'para…-v2')
quoted
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Missing closing "quote at line 3, column 642: … research paper synthesis, 长上下文, Gemini 2M token, 文档理解, 向量检索, 混合检索, RAG优化, 知识库. ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "slug"
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (Long Context RAG Analyzer) differs from the folder (long-context-rag-analyzer)
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. No external tools needed
- 100Steps. 32 steps
- 100Execution cost. Instruction body is 3817 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 627: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 32 items
- +4Has examples (13 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.