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AB anthropic

Anthropic Claude API integration — chat completions, streaming, vision, tool use, and batch processing via the Anthropic Messages API. Generate text with Claude Opus, Sonnet, and Haiku models, process images, use tool calling, and manage conversations. Built for AI agents — Python stdlib only, zero dependencies. Use for AI text generation, multimodal analysis, tool-augmented AI, batch processing, and Claude model interaction.

modbender/skill-library-mcp Agent Skills author: modbender MIT 2 files body ≈ 1 091 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Anthropic Claude API integration — chat completions, streaming, vision, tool use, and batch processing via the Anthropic Messages API.

As a process B 67/100 · Nearly there — weak spots: when it triggers, failures and branches, running it twice

IntegrationAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
67/100
Nearly there
Failures and branches w 10
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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 · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 67/100

    • 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. 4 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 10 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1091 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)
    • +2Single-language instructions
    • +3Description length 429: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 10 items
    • +3Output format is stated explicitly
    • +4Has examples (17 code blocks)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.