SKILLEMALL.ai

AC legal-guidance-vault

Helps a lawyer build and use a personalized Legal Guidance Vault — a local folder of structured, privilege-marked entries capturing legal guidance they've given, searchable later by topic, person, or product. Use this skill when the user says "set up my vault," "archive this meeting/email/thread/doc," "log the guidance I gave on [topic]," "save my notes from [meeting]," "what did I say about [topic]," "find the time I advised [person] on [topic]," or "search my vault for [topic]." Runs a setup interview to learn the user's tool stack (meeting notes, calendar, email, docs, messaging, vault location), then generates a customized vault prompt they can reuse in any future Claude session to start archiving and retrieving guidance.

lawve-ai/awesome-legal-skills Agent Skills author: lawve-ai 3 files body ≈ 2 478 tokens Open the sourcegithub.com↗ analyzed 63 min ago

Helps a lawyer build and use a personalized Legal Guidance Vault — a local folder of structured, privilege-marked entries capturing legal guidance they've…

As a process C 51/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

GeneratorGmailOutlookGoogle DocsGoogle DriveAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
89
Run on models
none yet
Process rating
C
51/100
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

    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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 51/100

    • 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
    • 40Consistency. Frontmatter name (legal-guidance-vault) differs from the folder (legal-guidance-vault-michael-cremata)
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 85Steps. 24 steps, 1 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 2478 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 15 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

    • +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
    • +5Description quotes 4 example trigger phrases
    • +3Description length 735: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 24 items
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 89.