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Glama

WizerAPI Contract Intelligence

Server Details

Review contracts for risks: summary, severity-rated flags, key terms, and clause coverage.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

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Tool DescriptionsA

Average 4.8/5 across 2 of 2 tools scored.

Server CoherenceA
Disambiguation5/5

The two tools have completely different purposes: analyze_contract performs contract analysis, while check_usage monitors API billing usage. No overlap or ambiguity.

Naming Consistency5/5

Both tools follow a consistent verb_noun pattern: analyze_contract and check_usage, with clear and predictable naming.

Tool Count3/5

With only two tools, the server feels sparse for a service named 'Contract Intelligence'. While analyze_contract is comprehensive, the lack of additional tools (e.g., list analyses, compare contracts) makes the scope narrow.

Completeness3/5

The primary tool provides a thorough first-pass review, but the server lacks retrieval or management tools for past analyses. No CRUD beyond creation exists, which may hinder workflows requiring history or comparison.

Available Tools

2 tools
analyze_contractFirst-pass contract reviewAInspect

First-pass review of ONE contract: plain-language summary, risk flags (with severity low|medium|high and explanations), key terms (parties, dates, term, termination notice, governing law, payment terms, auto-renewal), and presence/absence of 8 standard clauses with verbatim evidence excerpts. Input: raw contract text 100-150,000 chars (≤50,000 on the Free plan); optional title, counterparty, and document_type (msa|nda|sow|employment|lease|services|license|other). Raw text is never stored — only a content hash and the structured result. METERED — the most expensive WizerAPI operation: 12 AU + 1 AU per 1,250 chars (a 30,000-char contract ≈ 36 AU; the 150,000-char max ≈ 132 AU). Call check_usage BEFORE long documents. Re-analyzing byte-identical text in the same organization is 0 AU (cached: true). Every result reports its au_cost. Automated first-pass assistance, NOT legal advice.

ParametersJSON Schema
NameRequiredDescriptionDefault
textYes
titleNo
counterpartyNo
document_typeNo
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, description carries full burden. It discloses raw text is never stored (only hash and result), metered costing structure (12 AU + 1 per 1250 chars), caching for identical text, and that results report au_cost. Also includes disclaimer 'NOT legal advice'. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is somewhat long but each sentence adds value. Front-loads the output summary, then details input and behavior. Could be slightly more structured (e.g., bullet points), but still efficient and clear.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Comprehensively covers input constraints, costing, caching, non-storage, non-legal disclaimer, and output format. Despite no output schema, description details what the result includes (au_cost, summary, risk flags, etc.). Completely sufficient for agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% coverage, but description fully explains each parameter: text length constraints (100-150k chars, free plan limit of 50k), optional title/counterparty, and document_type enum with specific options and purpose for standard clause analysis. Goes well beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states 'First-pass review of ONE contract' and lists specific outputs (summary, risk flags, key terms, standard clauses). Distinguishes from sibling check_usage by mentioning it should be called before long documents and explaining costing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises to call check_usage before long documents and notes caching within organization to avoid cost. Implicitly indicates this is for initial automated assessment, not legal advice. Could be more direct about when not to use, but context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

check_usageCheck usage & quotaAInspect

Check the current billing period usage for YOUR WizerAPI organization: plan, included AU, used AU, remaining AU, overage so far, and the per-minute rate limit. Costs 0 AU and is never blocked by the session budget. Call this BEFORE large metered jobs (theme extraction over many reviews, long contracts) to confirm quota headroom, and AFTER quota errors to see where you stand.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses the tool is free (0 AU) and never blocked, and lists all returned data fields (plan, included AU, used AU, etc.), ensuring full behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, all front-loaded with key information. Every sentence serves a purpose: what it does, cost/blocking info, and when to use it. No redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description fully explains the tool's return values. Given zero parameters and a single sibling tool, the description is comprehensive and leaves no gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are no parameters (0 params, schema coverage 100%), so the description does not need to add parameter details. It compensates by explaining the output, adding value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses the specific verb 'Check' and resource 'current billing period usage', clearly stating the tool's purpose. It distinguishes from the sibling 'analyze_contract' by focusing on billing usage rather than contract analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly advises when to call the tool: before large metered jobs and after quota errors. It also highlights that it costs 0 AU and is never blocked, providing clear usage context and alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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