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ag_data_dedupe

Deduplicate JSON records exactly, optionally by key subset.

Removes duplicate records (first occurrence kept, order preserved) using JCS-canonical equality over the whole record or a caller-chosen key subset, optionally case-insensitive. Reports what was removed and why.

Deterministic, fixture-verified, free for guests (rate-limited; pass your Guild api_key to use your member budget). Returns the result plus a Guild-signed provenance envelope.

payload MUST match this JSON Schema: {"type": "object", "properties": {"records": {"type": "array", "minItems": 1, "maxItems": 5000}, "keys": {"type": "array", "items": {"type": "string"}}, "case_insensitive": {"type": "boolean"}}, "required": ["records"], "additionalProperties": false}

Output schema: {"type": "object", "properties": {"unique": {"type": "array"}, "kept": {"type": "integer"}, "removed": {"type": "integer"}, "duplicates": {"type": "array"}}, "required": ["unique", "kept", "removed", "duplicates"], "additionalProperties": false}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
payloadYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and excels: it discloses that first occurrence is kept, order is preserved, equality is JCS-canonical, and it reports what was removed and why. It also mentions determinism, guest rate limits, the option to use a member budget via api_key, and the Guild-signed provenance envelope—all beyond basic expectations.

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?

The description is moderately long but well-structured: a clear opening purpose, followed by behavior details, and then the required schema as a code block. Every prose sentence earns its place, and the embedded schema is necessary because it is not elsewhere in the input schema. It is slightly dense but appropriate for the tool's complexity.

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?

The description covers operation, parameter constraints, output, operational context (rate limits, api_key), and provenance. The output schema is present in the description, so return values are clear. No major gaps are apparent, especially given the lack of annotations and the tool's complexity.

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?

The input schema only specifies 'api_key' and an opaque 'payload' object with 0% coverage. The description compensates by embedding a full JSON Schema for 'payload', detailing required 'records' and optional 'keys' and 'case_insensitive'. It also explains that api_key is optional for guests but can be used for member budget, adding crucial meaning.

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 opens with a clear, specific verb+resource: 'Deduplicate JSON records exactly, optionally by key subset.' This distinguishes it from siblings like ag_json_canonicalize (which canonicalizes rather than removes duplicates) and ag_data_record_link (which links records).

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

Usage Guidelines3/5

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

The description implies usage context through the 'optionally by key subset' and 'case-insensitive' options, but it does not explicitly state when to use this tool vs alternatives or when not to use it. No comparison to sibling tools like ag_data_record_link is provided, so guidance is only implied.

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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TDQS

A4.1/5.0
Disambiguation4/5

Tools are grouped by prefix (ag_calc_, ag_data_, ag_json_, ag_table_, ag_text_), which helps disambiguate. However, some clusters like guild_search, guild_check, guild_risk_score, and guild_best_agent have overlapping goals (all find or evaluate agents), and guild_prove and guild_prove_verify are tightly coupled but distinct. Overall, most tools have clear purposes.

Naming Consistency4/5

The tools follow a consistent verb_noun or domain_verb pattern (e.g., ag_calc_stats, ag_data_dedupe, guild_search). The mix of ag_ and guild_ prefixes is slightly inconsistent, but within each group naming is uniform. No chaotic mixing of cases (all snake_case). Minor deduction for the split prefix.

Tool Count3/5

39 tools is on the high side for a single MCP server. While the tools are genuinely useful and cover distinct deterministic utilities plus guild trust operations, the count feels heavy. A more focused split (e.g., separate server for deterministic utilities vs. guild trust) could improve coherence.

Completeness5/5

The server covers a broad set of deterministic utilities (statistics, unit conversion, JSON, CSV, regex, date normalization) and a full trust/reputation workflow (register, search, check, risk score, escrow, attest, record, passport, verify, preflight). There are no obvious gaps: for the declared capabilities, the tool surface is comprehensive.