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AC isds-arbitrators

Arbitrator research tool for investor-State dispute settlement (ISDS). The tool can summarize arbitrators' experience, with deliverables grounded in primary documents; it can also help find arbitrators based on the issues faced in a particular case. Use when the user asks about an arbitrator ("tell me about arbitrator X", "X, Y and Z"), wants help choosing or shortlisting arbitrators for a case, or asks about appointments, dissents, issue track records (e.g. FET, expropriation), challenge risk, double-hatting, or tribunal composition. Profiles are grounded in the UNCTAD ISDS Navigator dataset plus targeted live lookups (ICSID); deep verification retrieves the actual decisions. Sibling of isds-research.

lawve-ai/awesome-legal-skills Agent Skills author: lawve-ai 14 files · 2 scripts body ≈ 3 638 tokens Open the sourcegithub.com↗ analyzed 76 min ago

Arbitrator research tool for investor-State dispute settlement (ISDS).

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency

AnalyzerExcelData and analyticsSecurityWriting and documentstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
99
Quality 40%
90
Run on models
none yet
Process rating
C
63/100
Has gaps
Inputs and preconditions w 11
30
Running it twice w 4
30
Result and completion w 14
40
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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • low Concealment en-hide-from-user references/deeper-analysis.md:11
      Instruction to hide actions from the user (negated — the text forbids it)
      **Intake first:** baseline defaults to the UNCTAD snapshot — one-line confirm without blocking, or bundled (marked as recommended default) into the single blocking intake call alongside depth, never a
      negated

    Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "owner"
    • note frontmatter-key unknown frontmatter key "last_verified"
    • note frontmatter-key unknown frontmatter key "freshness_window"
    • note frontmatter-key unknown frontmatter key "freshness_category"
    • note frontmatter-key unknown frontmatter key "verified_against"

    Process rating: all ten parameters 63/100

    • 30Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 2 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 40Consistency. Frontmatter name (isds-arbitrators) differs from the folder (isds-arbitrators-cameron-russell)
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 85Steps. 32 steps, 1 vague phrases
    • 100Failures and branches. 3 branches, has a failure section
    • 100Execution cost. Instruction body is 3638 tokens
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (4 tags): a typed call is more reliable

    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
    • +4No input/output examples
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 711: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 32 items
    • +4Reference files are cited in the instructions (3 of 4)
    • +3All 2 scripts are documented
    • +1License stated

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