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Glama

dns

by io.github.pipeworx-io

Recall

recall
Read-onlyIdempotent

Retrieve a value previously saved via remember, or list all saved keys (omit the key argument). Use to look up context the agent stored earlier — the user's target ticker, an address, prior research notes — without re-deriving it from scratch. Scoped to your identifier (anonymous IP, BYO key hash, or account ID). Pair with remember to save, forget to delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keyNoMemory key to retrieve (omit to list all keys)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "key": "user_research_topic"
+  },
+  {}
+]
  2. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare read-only and idempotent, and the description adds meaningful behavioral context: scoping to the agent's identifier (anonymous IP, BYO key hash, account ID) and the ability to list all keys when the argument is omitted. No contradiction with annotations; only minor details like return behavior are missing.

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?

Two sentences with front-loaded action, clear examples, and no filler. Every sentence adds value—action, use case, scoping, and workflow pairing.

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 simple one-parameter tool with no output schema, the description covers the core behavior, usage context, and scoping. It lacks explicit return-value details, but they are largely inferable for a retrieval tool, so it is nearly 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 coverage is 100% and the schema already explains the optional key and omit-to-list behavior. The description reinforces this with examples but does not add significant new parameter semantics beyond what the schema provides. Baseline 3 is appropriate.

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 states a specific verb ('Retrieve') and resource ('a value previously saved via remember'), and also covers the alternative behavior of listing all keys. It explicitly distinguishes from sibling tools by naming remember and forget as the counterparts.

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?

Provides concrete when-to-use guidance: 'Use to look up context the agent stored earlier' and gives examples like target ticker and research notes. It also points to alternatives: 'Pair with remember to save, forget to delete,' so the tool's role in the workflow is clear.

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

A3.8/5.0
Disambiguation2/5

ask_pipeworx and ask_pipeworx_beta are explicitly described as currently identical, creating real ambiguity between two tools. The polymarket cluster (arbitrage, edges, fill_risk, edge_tracker, kalshi_spread, bet_research) has overlapping edge-finding purposes that rely on reading long descriptions to separate, and the DNS tools are so few that an agent cannot tell this is a 'dns' server at all.

Naming Consistency2/5

The set mixes at least four naming conventions: bare verbs (remember, forget, subscribe), verb_noun (dns_lookup, validate_claim, discover_tools), noun phrases (entity_profile, deep_research, recent_alerts), and brand-prefixed families (ask_pipeworx_*, polymarket_*, pipeworx_*). Each cluster is internally consistent, but the overall pattern is incoherent, including stray names like reverse_dns that invert the verb_first convention.

Tool Count2/5

At 34 tools this exceeds the 25+ threshold for a heavy surface, and the count is wildly mismatched to the server's name: only 3 of 34 tools (dns_lookup, dns_lookup_all, reverse_dns) relate to DNS. The remaining 31 tools belong to unrelated domains (data research, prediction markets, memory, subscriptions, npm scanning), making the toolkit feel like a mislabeled grab-bag rather than a scoped server.

Completeness3/5

Judged against the server's stated 'dns' purpose, coverage is thin: read-only lookups only, with no WHOIS, DNSSEC, zone management, or write operations. Judged against the dominant inferred domain (a data-research/prediction-market platform), the surface is quite complete — query, grounded verification, deep research, profiles, comparisons, claim validation, discovery, subscriptions, alerts, and feedback all exist — though there is no tool to directly read a pipeworx:// citation URI.

Resources