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agent-exec

Read a stored object (free)

storage_read
Read-only

FREE: read back an object you own, as base64. This is how what you bought with storage_buy comes back to you over MCP. Ownership is proved by the paying wallet, with no account: send any placeholder signature once and the refusal returns details.expected -- the exact message to sign, in both forms (EIP-191 for a 0x wallet, ed25519 as 'solana::'). Complaints, questions, quote requests, or a service you wish we had: POST /feedback on this host -- free, no account. Every report is read and analysed daily; there is no individual reply.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe object id returned when it was bought.
nonceYesA value you have not used before on this route; it stops your signature being replayed.
signedAtYesUnix timestamp in seconds at which you signed; the server accepts a short window around now.
signatureYesYour ownership proof over the message the route names in details.expected.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Beyond annotations, it discloses the ownership-proving flow: no account, placeholder signature produces a refusal that carries details.expected, and the exact signable message formats for both wallet types. It also specifies the base64 return format. No contradiction with readOnly/destructive hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The first two sentences are front-loaded and efficient, but the final two sentences about '/feedback' and daily analysis are unrelated service promotion that does not help an agent invoke the tool. The core description is clear, but the irrelevant tail keeps it from being tighter.

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?

For a four-parameter, authenticated read with no output schema, the description explains the auth challenge/response, ownership requirement, and base64 result. It could include a success-response shape, but what an agent needs to compose a request is present.

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

Parameters4/5

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

Schema already covers all four parameters at 100%, so a baseline of 3 applies; the description adds useful auth-flow context for the signature parameter (placeholder signature, details.expected, EIP-191 vs ed25519 formats). The other parameters rely on the schema, which is acceptable.

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 a specific operation ('read back an object you own, as base64') and explicitly ties it to storage_buy as the retrieval counterpart, distinguishing it from sibling write/delete/renew tools. The verb and resource are unambiguous.

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?

Clearly frames the tool as the way to retrieve what was bought via storage_buy, establishing the primary use case and complementing the sibling set. It does not explicitly enumerate when to avoid it or compare to storage_list/storage_usage, so it stops at clear context with no exclusions.

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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