CryptoSocials

Describe archive

describe_archive

Read-only

Use when checking what readable evidence exists for a requested UTC period and scope. metrics=counts returns exact post and author counts; coverage adds asset, source, embedded and engagement diagnostics. This is not a mandatory first call, complete source history or a live collection watermark.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`text`	No
`date_to`	Yes	Exclusive UTC end; required.
`metrics`	No		coverage
`asset_ids`	No	Canonical asset IDs from resolve_assets, not tickers or provider IDs.
`chain_ids`	No	Coin chain IDs, e.g. solana, ethereum, base, robinhood. Includes confirmed stored V1, native and multichain associations; candidates, expired and unknown associations are excluded. Posts qualify through their attached coins.
`date_from`	Yes	Inclusive UTC start; required. Maximum window 366 days.
`has_media`	No
`asset_type`	No	Known asset relationship. With chain_ids, type must match on one of those chains; native and token relationships may coexist across chains. Unknown has no classified relationship.
`author_ids`	No	Canonical author IDs from search_authors, not X handles or user IDs.
`multichain`	No	True selects assets with at least two known chains. False means fewer than two KNOWN chains, not proven single-chain.
`post_types`	No
`evidence_class`	No	Filter standalone collected evidence versus retained embedded quote evidence; omitted includes both.
`exclude_post_types`	No	Exclude selected types; excluding original also excludes historical unknown labels, while excluding repost keeps ordinary unknown labels.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 4, 2026

addedInput schema / properties / text / properties / full_text_query / description

Added value: +"Space-separated AND, spaced OR, quoted phrases and minus exclusions. No stemming: agent and agents differ. Unquoted parentheses unsupported; repeat common terms, e.g. AI agent OR AI agents."

Changed2 schema fields changedOct 4, 2026

addedInput schema / properties / asset_ids / description

Added value: +"Canonical asset IDs from resolve_assets, not tickers or provider IDs."

addedInput schema / properties / author_ids / description

Added value: +"Canonical author IDs from search_authors, not X handles or user IDs."

Changed1 schema field changedOct 3, 2026

changedInput schema / properties / exclude_post_types / description

Previous value: -"Exclude only known types; excluding repost keeps unknown types."New value: +"Exclude selected types; excluding original also excludes historical unknown labels, while excluding repost keeps ordinary unknown labels."

Changed1 schema field changedSep 23, 2026

addedInput schema / properties / metrics

Added value: +{
+  "default": "coverage",
+  "enum": [
+    "counts",
+    "coverage"
+  ]
+}

First observedSep 21, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already declare the read-only, non-destructive, non-idempotent profile. The description adds genuine behavioral context beyond them: what metrics=counts vs coverage returns, and the important caveat that this is not a complete source history or a live watermark, which sets expectations about data completeness.

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?

Three tightly written sentences, front-loaded with usage guidance, then output modes, then exclusions. No filler; each sentence carries distinct information.

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 13-parameter read-only tool with no output schema, the description usefully explains what is returned (post/author counts, coverage diagnostics) and disclaims completeness limits. Given the schema carries most filter detail, this is nearly sufficient, though the complex filtering surface could use slightly more framing.

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 69%, and the schema already documents most parameters (including the detailed full_text_query and chain_ids semantics). The description adds meaning only for the metrics parameter, explaining the difference between counts and coverage, but does not compensate for the remaining undocumented filters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific purpose — checking what readable evidence exists for a UTC period and scope — and clarifies its two output modes (counts vs coverage diagnostics). It is clear what the tool does, but it does not distinguish itself from siblings such as aggregate_posts or get_usage, leaving the agent to infer the boundary.

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?

It gives an explicit when-to-use condition ('checking what readable evidence exists for a requested UTC period and scope') plus clear when-not guidance ('not a mandatory first call, complete source history or a live collection watermark'). It stops short of naming a specific alternative sibling to use instead.

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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