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BC local-falcon

Expert guidance on AI Visibility and Local SEO from Local Falcon, the pioneer of geo-grid rank tracking. Provides deep knowledge on optimizing for AI search platforms (ChatGPT, Gemini, AI Mode, AI Overviews, Grok), local pack rankings, Google Business Profile optimization, and actionable strategies for agencies, enterprises, and SMBs. Includes guidance on using Local Falcon's MCP server for data-driven analysis.

modbender/skill-library-mcp Agent Skills author: modbender MIT 10 files body ≈ 5 489 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Expert guidance on AI Visibility and Local SEO from Local Falcon, the pioneer of geo-grid rank tracking.

As a process C 56/100 · Has gaps — weak spots: inputs and preconditions, consistency, progress reporting

ProcedureAI and agentsMarketingData and analyticstype 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
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
65
Run on models
none yet
Process rating
C
56/100
Has gaps
Inputs and preconditions w 11
0
Progress reporting w 2
0
Consistency w 8
40
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 10. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 5489 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "display_name"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "documentation"
  • note frontmatter-key unknown frontmatter key "repository"
  • note frontmatter-key unknown frontmatter key "categories"
  • note frontmatter-key unknown frontmatter key "capabilities"
  • note frontmatter-key unknown frontmatter key "mcp_integration"
  • note frontmatter-key unknown frontmatter key "triggers"
  • note frontmatter-key unknown frontmatter key "invocation"

Process rating: all ten parameters 56/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 40Consistency. Frontmatter name (local-falcon) differs from the folder (local-visibility-skill)
  • 50When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (web, node) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70Failures and branches. 5 branches
  • 70Execution cost. Instruction body is 5489 tokens
  • 85Steps. 93 steps, 1 vague phrases
  • 100Running it twice. Mutating operations check current state
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 17 top-level sections: this looks like several domains in one skill

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)
  • -246 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 415: enough signal without eating the budget
  • +4Structure: 53 headings
  • +3Step-by-step instructions: 93 items
  • +3Output format is stated explicitly
  • +4Has examples (9 code blocks)
  • +4Reference files are cited in the instructions (4 of 4)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 65.