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Glama

Base64

by io.github.pipeworx-io

Discover Tools

discover_tools
Read-onlyIdempotent

Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoAlias for query.
taskNoAlias for query.
limitNoMaximum number of tools to return (default 20, max 50)
queryYesNatural language description of what you want to do (e.g., "analyze housing market trends", "look up FDA drug approvals", "find trade data between countries"). Accepts task, q, description, search as aliases.
searchNoAlias for query.
descriptionNoAlias for query.

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destuctiveHint=false, so safety is covered. The description adds that it returns top-N most relevant tools with full schemas and curated examples, ready to call—useful behavioral context beyond annotations.

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 front-loaded with purpose and usage guidelines. It lists many domains in a dense format but remains understandable. Slightly wordy but effective.

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 discovery tool with 6 parameters (many aliases) and no output schema, the description explains the return value (names, descriptions, schemas with examples) and readiness to call. It does not mention pagination or rate limits, but overall complete.

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 description coverage is 100%, so the schema already documents all parameters including aliases. The description does not add significant parameter-level meaning beyond what the schema provides, meeting the baseline for high coverage.

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 the tool finds tools by describing a data or task, listing specific domains (SEC filings, financials, FDA drugs, etc.). It explicitly distinguishes itself from sibling tools by instructing to call this FIRST to see the option set.

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?

Explicitly says 'Call this FIRST when you have many tools available and want to see the option set', providing clear when-to-use context. It does not explicitly state when not to use, but the implied purpose is sufficient.

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

All Base64 toolsInspect
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TDQS

A3.7/5.0
Disambiguation2/5

Several tool groups have unclear boundaries: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, polymarket_edges / polymarket_arbitrage / polymarket_edge_tracker / polymarket_fill_risk / polymarket_kalshi_spread / bet_research all push prediction-market opportunities and can be confused, and ai_visibility_check is nested inside scan_competitor_ai_presence. discover_tools and suggest_questions also overlap as tool-discovery entry points.

Naming Consistency3/5

Everything is snake_case and mostly descriptive, but conventions are mixed: verb-first names (resolve_entity, validate_claim, compare_entities, search_within) sit beside noun-first names (entity_profile, recent_changes, bet_research, polymarket_edges), and brand-prefixed tools (pipeworx_feedback, pipeworx_trending) have unprefixed functional siblings (list_subscriptions, recent_alerts). The two actual Base64 tools (base64_encode, base64_decode) don't match the dominant Pipeworx naming style at all.

Tool Count2/5

33 tools is heavy for any single server, and the mismatch is extreme: the server is named 'Base64' yet only 2 of 33 tools relate to encoding/decoding — the other 31 form a sprawling data-research platform. Even judged as a data platform, the count exceeds the comfortable range and includes near-duplicates (the ask_pipeworx family, the Polymarket family).

Completeness4/5

The factual-data surface is well covered: query, grounded lookup, deep research, entity profiling, comparison, claim verification, entity resolution, subscriptions (subscribe/list/unsubscribe/recent_alerts), memory (remember/recall/forget), feedback, and tool discovery all exist with no obvious dead ends. The Base64 encoding domain is also complete (encode/decode across four variants). Minor gaps exist (e.g., no way to update a profile or edit memory entries) but they're workable.

Resources