SKILLEMALL.ai

BF research-agent

Conduct open-ended research on a topic, building a living markdown document。Supports。Use when 需要文件处理、文档转换、格式互转、内容提取时使用。不适用于加密文件破解。适用于独立开发者、企业团队和自动化工作流场景。 功能涵盖: agent(代理)。

ClawHub Hermes author: 天轰穿 v1.0.1 MIT-0 2 files body ≈ 1 265 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process F 35/100 · Will not run — References files that are not bundled: assets/research-agent_template

GeneratorAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
84/100
safety, quality, tests
Safety 60%
100
Quality 40%
60
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: assets/research-agent_template
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
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.
  2. The text references files that are not there: add them or drop the references.
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

  • warning frontmatter-yaml SKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 11, column 14: description: Conduct open-ended research on a topic, building a living markdown… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-long-hermes description is 170 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning missing-ref reference to a missing file: assets/research-agent_template
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "summary_zh"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "pricing_tier"

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: assets/research-agent_template
  • 0Tools and files. 1 referenced file(s) missing: assets/research-agent_template
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 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
  • 100Steps. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1265 tokens
  • 100Running it twice. No mutating operations
  • low 14 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)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 170: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (2 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 60.

External checks

ClawHub: suspicious
The skill is not clearly malicious, but it asks for broad read, write, command execution, and API-related authority for a very loosely scoped research and automation purpose.
LLM: suspicious (medium) · 22 Aug 2026