Skip to main content
Glama

agent-guild

by io.github.AgentTanuki

ag_json_diff

Structural diff of two JSON values with per-path changes.

Compares two JSON values and returns added/removed/changed paths (JSON-Pointer-style), capped at 500 changes. Use to verify an agent's output changed only what it was asked to.

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": {"a": {}, "b": {}}, "required": ["a", "b"], "additionalProperties": false}

Output schema: {"type": "object", "properties": {"equal": {"type": "boolean"}, "changes": {"type": "array"}, "change_count": {"type": "integer"}}, "required": ["equal", "changes", "change_count"], "additionalProperties": false}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNo
payloadYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description fully discloses behavior: deterministic, fixture-verified, capped at 500 changes, rate-limited for guests with optional api_key, and a Guild-signed provenance envelope. It also embeds the required payload schema and output schema. This far exceeds minimum disclosure and gives the agent confidence in side effects and limits.

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 front-loaded with purpose, then logically moves to use case, behavior, and schemas. Each sentence contributes critical information; the included JSON schemas replace verbose prose. It is well-structured and not bloated.

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 tool is fully specified: input payload schema, output schema, change cap, determinism, provenance, and authentication context. The presence of the output schema means return values need no further explanation. For a complex diff tool, this is complete.

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?

Despite 0% schema description coverage, the description compensates by providing the complete payload schema with required 'a' and 'b' fields. It also explains api_key usage in the rate-limit context. This gives agents full parameter meaning beyond names and types.

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 'Structural diff of two JSON values with per-path changes,' using a specific verb and resource. It distinguishes itself from sibling JSON tools like validate, canonicalize, and path_extract by focusing on diffing. The later mention of 'added/removed/changed paths' reinforces the unique purpose.

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?

The description explicitly states when to use: 'Use to verify an agent's output changed only what it was asked to.' This gives clear context, though it does not name alternatives or provide exclusion criteria. The sibling tools are not referenced, missing the 'vs alternatives' element that would earn a 5.

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

All agent-guild toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources