SKILLEMALL.ai

CF financial-financial-analysis

Core financial modeling and analysis tools: DCF, comps, LBO, 3-statement models, competitive analysis, and deck QC

ClawHub Agent Skills author: paudyyin v1.0.0 MIT-0 3 files body ≈ 8 234 tokens Open the sourceclawhub.ai analyzed 3 d ago

Core financial modeling and analysis tools: DCF, comps, LBO, 3-statement models, competitive analysis, and deck QC

As a process F 40/100 · Will not run — References files that are not bundled: examples/comps_example.xlsx, examples/LBO_Model.xlsx, assets/template.pptx

AnalyzerExcelPowerPointSoftware developmentData and analyticsFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
C
74/100
safety, quality, tests
Safety 60%
100
Quality 40%
36
Run on models
none yet
Process rating
F
40/100
Will not run
References files that are not bundled: examples/comps_example.xlsx, examples/LBO_Model.xlsx, assets/template.pptx
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. 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.
  3. 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: 3. 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 3, column 14: description: Core financial modeling and analysis tools: DCF, comps, LBO, 3-sta… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • warning body-long SKILL.md body ≈ 8234 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: examples/comps_example.xlsx
  • warning missing-ref reference to a missing file: examples/LBO_Model.xlsx
  • warning missing-ref reference to a missing file: assets/template.pptx
  • note frontmatter-key unknown frontmatter key "source"

Process rating: all ten parameters 40/100

Will not run. References files that are not bundled: examples/comps_example.xlsx, examples/LBO_Model.xlsx, assets/template.pptx
  • 0Tools and files. 3 referenced file(s) missing: examples/comps_example.xlsx, examples/LBO_Model.xlsx, assets/template.pptx
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 18 mutating operations with no state check
  • 40Execution cost. Instruction body is 8234 tokens: crowds the task out of the window
  • 50When it triggers. No condition that starts the skill
  • 85Steps. 114 steps, 3 vague phrases
  • 100Failures and branches. 4 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 28 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)
  • +3Description length 114: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +4Structure: 73 headings
  • +3Step-by-step instructions: 114 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 36.

External checks

ClawHub: clean
This is a Markdown-only financial research workflow skill with no hidden execution, installer scripts, credential handling, or persistence found.
LLM: benign (high) · VirusTotal: · 19 Jun 2026