Skip to main content
Glama

Realestate

by io.github.pipeworx-io

Send Pipeworx Feedback

pipeworx_feedback

Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a claim_token; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNobug = something broke or returned wrong data. feature = a new tool or capability you wish existed. data_gap = data Pipeworx does not currently expose. praise = positive note. other = anything else.
contextNoOptional structured context: which tool, pack, or vertical this relates to.
messageNoYour feedback in plain text. Be specific (which tool, what error, what data was missing). 1-2 sentences typical, 2000 chars max.
claim_tokenNoRead the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.

Schema Changelog

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

  1. Changed2 schema fields changed
    • addedInput schema / properties / claim_token
      Added value: +{
+  "description": "Read the reply to a report you filed earlier: pass the `pwfb_…` token that filing returned, with no other arguments. Returns the status and, once resolved, what actually changed.",
+  "type": "string"
+}
    • removedInput schema / required
      Removed value: -[
-  "type",
-  "message"
-]
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the annotations, the description discloses important behavioral details: rate limiting ('Rate-limited to 5 per identifier per day'), the claim_token workflow ('Filing without an account returns a claim_token; pass it back later...'), cost implications ('Free; doesn't count against your tool-call quota'), and the fact that reports are read daily and influence roadmap. No contradictions with 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 long but every sentence serves a distinct purpose: core purpose, when to use, scope exclusions, message guidelines, token workflow, rate limits, and cost. It is front-loaded with the main purpose and structured logically. Slightly verbose, but the complexity (multi-purpose, exclusions, two-phase token) justifies the length.

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?

Given there is no output schema, the description adequately explains the return behavior (claim_token and later status updates). It covers the tool's full lifecycle, including exclusions, rate limits, and practical tips. For a feedback tool with a complex token mechanism and clear differentiation among 30+ siblings, the description is complete and self-sufficient.

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 the schema already documents all parameters. However, the description adds practical meaning: it explains the claim_token's revisit syntax ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})'), specifies that claim_token should be used with no other arguments, and advises on message content ('Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt'). This goes beyond the schema's dry descriptions.

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's purpose: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' This uses a specific verb and resource (feedback for Pipeworx tools), and it is distinct from sibling tools which are all research/query-oriented. The differentiation from siblings is further reinforced by the explicit scope of 'tools served by this Pipeworx connection.'

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 provides explicit when-to-use guidance: 'Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise).' It also clearly states when NOT to use it: 'if the tool came from a different MCP server in your client... file it with that server instead.' This is exemplary usage guidance.

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

All Realestate toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools occupy the same natural-language lookup niche: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer factual questions, and the beta tool is currently described as identical to the stable router. Prediction-market edge detection also fans out across bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, and polymarket_fill_risk, so an agent can easily select the wrong one.

Naming Consistency4/5

Most names follow a predictable snake_case action-first pattern (ask_pipeworx, resolve_entity, subscribe, unsubscribe) with helpful domain prefixes for polymarket_*, realestate_*, and pipeworx_*. Minor deviations exist—entity_profile is noun-first, ask_pipeworx lacks an underscore, and remember/forget/recall are bare verbs—but they do not create real confusion.

Tool Count2/5

33 tools is well above the coherence sweet spot and the rubric's 25+ threshold. The count is inflated by auxiliary platform utilities (feedback, trending, memory, subscriptions, llms.txt generation, npm scanning) that are unrelated to the Realestate name and make the tool surface feel like a full platform rather than a focused MCP server.

Completeness2/5

For a server named Realestate, the surface is only minimally complete: realestate_municipalities and realestate_transactions cover Japanese transaction lookups, but there are no tools for property listings, property details, pricing estimates, or typical real-estate workflows. Even viewed as a broad data platform, the set is read-heavy with no create/update/delete operations beyond memories and subscriptions, leaving significant workflow gaps.

Resources