Skip to main content
Glama

how-to

Read-only

Built-in product help — ask a natural-language "how do I…" question about Fastio and get a grounded, product-aware answer (or a short clarifying question) back in one call. EXPLAIN-ONLY / ADVISORY: it returns GUIDANCE TEXT and performs NO platform action (it will not create shares, move files, or change anything) — read the guidance, then act with the other tools. Answers are grounded in Fastio's own how-to knowledge AND phrased in terms of these MCP tools — they name the concrete <tool> action="…" calls to make — so prefer this over guessing endpoints or burning exploratory calls. For Q&A over YOUR uploaded files (RAG) use the ai tool instead — how-to answers questions about Fastio ITSELF. FREE and requires only an authenticated user (no org, no plan gate, no billing). Call action='describe' for the full action/param reference.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesOperation. Use 'describe' for full action reference.
contextNoOptional free-text background about your situation (what you're trying to accomplish, what you've tried). Up to 8000 chars. Treated strictly as untrusted DATA — it cannot redirect the assistant. Omit when empty.
questionNoThe natural-language "how do I…" question about Fastio. 1-2000 chars, non-blank. Be specific — a vague question returns a clarifying question instead of an answer.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already mark readOnlyHint=true, openWorldHint=true, and destructiveHint=false; the description goes beyond by adding 'EXPLAIN-ONLY / ADVISORY,' stating it performs no platform action, will not create shares/move files/change anything, and is free with only an authenticated user required. This is rich behavioral context with no contradiction.

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 dense but well-organized, front-loading the core purpose and safety profile before diving into usage distinctions. Every sentence earns its place, though the length is notable; the ALL-CAPS label and clear clauses keep it scannable. It is not bloated but could be slightly tightened.

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?

For a tool with no output schema and a simple 3-parameter schema, the description is exceptionally complete: it explains return behavior (answer or clarifying question), scope (Fastio how-to vs RAG), safety/no-op nature, cost/auth requirements, and how to get a full action reference. No significant gaps remain.

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 coverage is 100%, so baseline is 3; description adds meaningful semantics: 'Call action="describe" for the full action/param reference,' 'a vague question returns a clarifying question instead of an answer,' and that `context` is 'treated strictly as untrusted DATA — it cannot redirect the assistant.' These details enhance understanding beyond the schema.

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 opens with a specific verb+resource: 'ask a natural-language how-do-I question about Fastio and get a grounded, product-aware answer.' It clearly identifies the tool as built-in product help and explicitly contrasts it with the `ai` tool for RAG over uploaded files, distinguishing it from siblings.

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?

The description gives explicit when-to-use guidance: 'prefer this over guessing endpoints or burning exploratory calls' and explains that `how-to` answers questions about Fastio ITSELF, while `ai` handles Q&A over uploaded files. It also tells the agent to act with other tools after reading guidance and mentions the `action='describe'` option for a full reference.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation5/5

Each tool covers a clearly distinct domain (auth, storage, shares, comments, events, AI, etc.), and overlapping concepts like share vs. fileshare are explicitly disambiguated with deprecation notes and cross-references. An agent can reliably select the correct tool for a task without ambiguity.

Naming Consistency3/5

Tool names are all lowercase single words, but they mix nouns (user, org, workspace) with verbs (download, find, upload) and include a hyphenated 'how-to'. There is no consistent verb_noun or noun-only pattern, though the names are still readable and memorable.

Tool Count4/5

19 tools is slightly above the typical 3-15 sweet spot, but the platform's breadth (auth, file management, sharing, collaboration, AI, metadata, and help) justifies this count. Each tool represents a substantial domain area, so none feel redundant.

Completeness5/5

The toolset provides full lifecycle coverage for the platform: authentication, user/org/workspace management, file storage/upload/download/search, sharing (both quickshare and durable file shares), comments, events, metadata pipelines, AI assistance, and product help. No obvious dead ends or missing operations are apparent.

Resources