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fetch_aifeed

Fetch web pages as token-budgeted AIFeed Markdown or MAKO, with optional signature verification to ensure content authenticity.

Instructions

Fetch a page as token-budgeted AIFeed Markdown/MAKO with permissions and optional signature verification.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPage URL (https)
profileNoContent profile (default aimd)
max_tokensNoToken budget; body is truncated to fit
publicKeyValueNoed25519:… key to verify the page signature

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It discloses token-budgeting and optional signature verification, which is helpful. However, it does not clarify that fetching is likely read-only, what happens on permission failure, or the implications of signature verification failure. The phrase 'with permissions' is vague—does the tool check permissions or request them?

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 a single sentence, front-loaded with the primary action. It packs a lot of specifics without fluff. However, the phrase 'with permissions' is ambiguous and could be clearer, but overall it is efficient.

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?

The tool has 4 parameters, no output schema, and no annotations. The description does not explain return format, error conditions, or prerequisites. An agent would not know whether the page must be accessible, what happens if signature verification fails, or how token truncation affects output. It leaves significant gaps for a complex fetch operation.

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 coverage is 100%, so all parameters are already documented. The description adds context by linking 'token-budgeted' to max_tokens, 'AIFeed Markdown/MAKO' to profile, and 'signature verification' to publicKeyValue. This is useful but not extensive; it essentially restates schema meanings in a sentence. Baseline 3 is appropriate.

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 states a specific verb ('Fetch'), a resource ('a page'), and the output format ('AIFeed Markdown/MAKO') with additional features (permissions, signature verification). It clearly distinguishes from siblings like verify_manifest and list_assets, which are about verification and asset listing, not page fetching.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. It does not mention any context like 'use this to retrieve content' or contrast with sibling operations. The purpose is clear but the description leaves it to the agent to infer when to call it.

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