SKILLEMALL.ai

AC openclaw-indian-advocate

AI legal assistant for Indian advocates and lawyers. Use this skill whenever an Indian advocate needs help with legal work: drafting legal notices, vakalatnamas, plaints, written statements, bail applications, affidavits, petitions (writ, civil, criminal), FIR complaints, legal opinions, or any Indian court document. Also triggers for Indian statutes (IPC/BNS, CrPC/BNSS, IEA/BSA, Companies Act, GST, Arbitration), case law research, client intake, cause list management, court diary, fee notes, legal memos, or reading/analysing uploaded case files, judgments, charge sheets, or client documents. Triggers on: "my client", "HC", "SC", "district court", "sessions court", "NCLT", "DRT", "tribunal", "advocate", "vakil", "matter", "brief", or any Indian legal proceeding. Handles post-2024 BNS/BNSS/BSA reforms with dual-citation of old and new laws automatically.

ClawHub Agent Skills author: Dhiraj Patra v1.0.0 MIT-0 8 files body ≈ 1 089 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerResearchInfrastructureCustomer supporttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
C
57/100
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: 8. 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 57/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 34 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1089 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Description length 865: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 34 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (5 of 5)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This is a text-only Indian legal-assistant skill whose sensitive document handling is disclosed and aligned with legal drafting and practice-management work.
    LLM: benign (high) · VirusTotal: · 29 May 2026