SKILLEMALL.ai

AB x

Search X (Twitter) posts and retrieve known post details and replies through the official Gecho Bridge MCP tools. Use for keyword monitoring, post research, author context, engagement signals, and reply analysis.

ClawHub Hermes author: Gecho AI v1.1.37 MIT-0 3 files body ≈ 3 770 tokens Open the sourceclawhub.ai analyzed 3 d ago

Search X (Twitter) posts and retrieve known post details and replies through the official Gecho Bridge MCP tools.

As a process B 70/100 · Nearly there — weak spots: consistency, running it twice

AnalyzerInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
81
Run on models
none yet
Process rating
B
70/100
Nearly there
Consistency w 8
0
Running it twice w 4
30
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

  1. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 212 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)

Process rating: all ten parameters 70/100

  • 0Consistency. Frontmatter name (x) differs from the folder (gecho-x-research)
  • 30Running it twice. 2 mutating operations with no state check
  • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 87 steps
  • 100Failures and branches. 4 branches, has a failure section
  • 100Execution cost. Instruction body is 3770 tokens
  • 100Progress reporting. Reports progress
  • low 18 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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 212: enough signal without eating the budget
  • +4Structure: 34 headings
  • +3Step-by-step instructions: 87 items
  • +3Output format is stated explicitly
  • +4Has examples (8 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 81.

External checks

ClawHub: clean
This skill is a disclosed, read-only X research workflow, with the main caution that saved post and reply JSON may contain personal data.
LLM: benign (high) · VirusTotal: · 22 Aug 2026