SKILLEMALL.ai

AC private-equity

股权投资技能套件:审条款、尽调清单、投决备忘录、测收益、筛项目、退出分析。 审条款: 帮我看下这个TS, 帮我审下SPA条款, term sheet, 审TS, 审SPA; 尽调清单: 尽调清单, due diligence, DD checklist; 投决备忘录: 帮我写投决纪要, 帮我出IC Memo, 投决备忘录, 投委会; 测收益: 帮我算下IRR, 帮我测下回报率, MOIC, DPI, 算IRR; 筛项目: 筛项目, deal sourcing, 项目初筛; 退出分析: 退出分析, 退出路径, IPO退出。

ClawHub Agent Skills author: ebandao v0.1.0 MIT-0 9 files body ≈ 1 113 tokens Open the sourceclawhub.ai analyzed 2 d ago

股权投资技能套件:审条款、尽调清单、投决备忘录、测收益、筛项目、退出分析。 审条款: 帮我看下这个TS, 帮我审下SPA条款, term sheet, 审TS, 审SPA; 尽调清单: 尽调清单, due diligence, DD checklist; 投决备忘录: 帮我写投决纪要, 帮我出IC Memo…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

Templatetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
C
53/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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.
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: 9. 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")

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 23 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1113 tokens
  • 100Running it twice. No mutating operations

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 263: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 23 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (6 of 6)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.

External checks

ClawHub: suspicious
This is a coherent private-equity workflow skill, but it can write confidential deal materials to Notion when connected without an explicit consent gate.
LLM: suspicious (high) · VirusTotal: · 15 Aug 2026