NaN Mesh

nanmesh.entity.get

Read-only

Get full details for a specific entity by slug or UUID. Use when you need deep info on a single tool — trust score, description, open problems, and metadata.

AI-native (2026-05-12): pass format='agent' (+ optional task_type, stack) to get the firehose:
evidence-aware confidence_decomposition, known_failure_modes, recent_execution_reports, and a
network_evidence block showing whether this entity has real operational reports or still needs
first evidence.

Input Schema

TableJSON Schema

Name	Required	Description
`slug`	Yes	Entity slug (e.g. 'stripe', 'mysterypartynow') or UUID
`stack`	No	Comma-separated stack tags for filtering recent_execution_reports (e.g. 'nextjs,supabase'). Only used when format='agent'.
`format`	No	Pass 'agent' to opt into the ai-native firehose (evidence-aware confidence_decomposition, known_failure_modes, recent_execution_reports, network_evidence, schema_version). Default returns the summary.
`task_type`	No	Narrow confidence to a task (e.g. 'subscription_billing', 'oauth'). Only used when format='agent'.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already mark it readOnly, lowering the bar. The description adds meaningful behavioral context for the 'agent' format – the firehose fields and the network_evidence block indicating whether the entity has real operational reports or needs first evidence. This goes beyond annotations, though it doesn't cover errors or rate 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?

Two efficient paragraphs: the first front-loads purpose and usage, the second presents the agent-mode extras in a readable list. Every sentence earns its place, with no fluff or redundancy.

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

Completeness4/5

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

Given that an output schema exists and readOnly is set, the description covers the default and agent modes, and the significance of the network_evidence field. It's sufficiently complete for a get-details tool, though it could mention edge cases or explicitly point to siblings for other use cases.

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

Parameters3/5

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

Schema description coverage is 100%, so each parameter is already documented. The description mainly restates the format='agent' option and lists its effects, which the schema also mentions. The network_evidence explanation is useful but pertains to output, not parameter meaning, so baseline 3 applies.

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?

States 'Get full details for a specific entity by slug or UUID' – a specific verb+resource. Differentiates from siblings by noting 'deep info on a single tool' and listing fields (trust score, description, open problems, metadata), which contrasts with search/compare.

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 says 'Use when you need deep info on a single tool', giving clear context. However, it doesn't name alternative sibling tools (like search or compare) or state when not to use this tool, so it stops short of full when/when-not guidance.

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

A4/5.0

Disambiguation3/5

Most tools have distinct domains (agent, entity, platform, post, trust), but trust.favor and trust.report_outcome both serve as quick up/down votes with only weight/auth differences, causing potential misselection. entity.search and entity.recommend also overlap in answering 'what should I use for X?', though descriptions mitigate this somewhat.

Naming Consistency4/5

Names consistently follow a nanmesh.<domain>.<action> pattern with lowercase underscores. While some actions are nouns (problems, stats) rather than verbs, the format is uniform and predictable, making it easy to infer functionality.

Tool Count5/5

13 tools is within the ideal range and each serves a distinct aspect of the trust network: registration, entity discovery, trust expression, posting, and stats. No tool feels superfluous, and the scope is well matched to the server's purpose.

Completeness4/5

Core workflows are covered: search, get, problems, recommend, compare, trust voting, posting, and stats. However, the activate_key tool references nanmesh.agent.challenge as STEP 1, but that tool is missing, breaking the described activation flow. Additionally, there is no way to retrieve a post after creating it, though that is a minor gap.

Resources

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