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jorgenclaw

Pay per Call Nostr service for AI Agents MCP

nostr_get_notes

Fetch recent Nostr notes by author or hashtag using a pay-per-call service for AI agents with verifiable audit trails.

Instructions

Fetch recent kind 1 notes by author or hashtag. Price: 5 sats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
authorNoAuthor npub or hex pubkey
hashtagNoHashtag to search (without #)
limitNoMax results (default 10, max 20)
payment_preimageNoLightning payment preimage (64 hex chars)
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses a cost ('Price: 5 sats'), which is a behavioral trait, but lacks other critical details such as rate limits, authentication needs, error handling, or what 'recent' means temporally. The description does not contradict annotations (none exist).

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 extremely concise and front-loaded with essential information (purpose and cost) in just two sentences. Every word earns its place, with no wasted text or redundancy.

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

Completeness2/5

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

Given the tool's complexity (4 parameters, no annotations, no output schema), the description is incomplete. It lacks details on return values, error conditions, or how the payment preimage relates to the cost mentioned. The cost disclosure is helpful, but more behavioral and output context is needed for adequate completeness.

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 the schema already documents all parameters thoroughly. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain interactions between parameters like author vs hashtag). Baseline 3 is appropriate as the schema does the heavy lifting.

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 clearly states the tool's purpose with specific verbs ('fetch') and resources ('recent kind 1 notes'), and distinguishes it from siblings by specifying the type of content (notes vs profiles, events, etc.). It also mentions the cost ('5 sats'), which is unique among sibling tools.

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 for fetching notes by author or hashtag, but does not explicitly state when to use this tool versus alternatives like 'nostr_fetch_profile' or 'nostr_post_note'. It provides some context (e.g., 'recent'), but lacks explicit exclusions or comparisons to other tools.

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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