Fillin

glyph_search

Read-onlyIdempotent

Same as fillin_query, but returns the result pieces rendered as photo glyph image(s) — dense, vision-readable pages — followed by a JSON citation index ({n, source, url, title, published_at, page}).

Read the image(s) directly with your vision capability; use the citation
index to attribute or follow up. Glyphs are for comprehension and
fact-extraction, not verbatim quotes (vision models paraphrase) — open the
url for exact text. Billed at the flat /query rate; rendering is free.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`k`	No	Number of documents to retrieve (1-12).
`tier`	No	Glyph density tier: 6x \| 10x \| 15x.	10x
`query`	Yes	Natural-language search query, max 512 chars.
`cutoff`	Yes	Training cutoff as ISO-8601 date (e.g. 2026-01-01). Documents on or before this date are excluded.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

TDQS

A4.7/5.0

Behavior5/5

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

Beyond the readOnlyHint, the description discloses the output structure (images + citation index), the billing model (flat /query rate, free rendering), and a behavioral caveat (vision models paraphrase), which is useful context. It does not contradict annotations.

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 three sentences, front-loaded with the core function ('Same as fillin_query, but...') and efficiently packs output format, usage tips, and billing into a compact text.

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

Completeness5/5

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

With an output schema present and annotations covering read-only behavior, the description adds enough operative details—how to read the images, use the citation index, and handle paraphrasing—to make the tool fully actionable.

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?

The input schema already provides complete descriptions for all four parameters (100% coverage), including query, cutoff, k, and tier. The description adds no parameter-level detail, so the score is at baseline 3.

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 that this tool performs the same search as fillin_query but returns results as photo glyph images plus a JSON citation index, distinguishing it from its sibling. It specifies the output artifacts and their purpose.

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

Usage Guidelines5/5

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

It explicitly frames this as an alternative to fillin_query with visual output, and gives a when-not-to-use directive: glyphs are for comprehension and fact-extraction, not verbatim quotes, suggesting opening the URL for exact text. This provides clear guidance on selecting this tool over the sibling.

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

A3.9/5.0

Disambiguation2/5

Several tools overlap significantly: fillin_query, glyph_search, and retrieve_auto all perform post-cutoff retrieval and differ only in output substrate, and fillin_health and fillin_stats both report corpus stats. This creates ambiguity for agents choosing between them.

Naming Consistency3/5

Tool names mix three conventions: fillin_* (fillin_query, fillin_mint), query_* (query_cves, query_papers), and bare names (encode, glyph_search, retrieve_auto). While readable and mostly snake_case, the lack of a uniform prefix or verb pattern makes naming inconsistent.

Tool Count4/5

14 tools is within the acceptable range for a multi-feature server, but there is some redundancy (two health/stats tools, three retrieval variants), making the count feel slightly inflated.

Completeness5/5

The server covers retrieval (text/glyph/auto), encoding, marketplace operations (mint, search, buy), and domain-specific queries (CVEs, frontier AI, markets, papers), with no obvious missing capabilities.

Resources

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