Skip to main content
Glama

Traject Ecommerce

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.

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only declare non-read-only, non-open-world, non-idempotent, non-destructive traits. The description goes well beyond this by explaining the claim_token return and follow-up flow, the daily rate limit of 5 per identifier, that feedback is free and does not count against tool-call quota, and how the team processes digests.

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 carries distinct information: purpose, use cases, exclusions, return contract, rate limit, and quota. It is front-loaded with the core action, and while dense, it contains no filler. A slightly structured layout could improve readability, but each sentence earns its place.

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?

Even though there is no output schema, the description fully specifies the return behavior (claim_token), the routing constraints, content guidance, and operational limits. The tool has moderate complexity, and the description addresses all aspects an agent needs to invoke it correctly and interpret results.

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 baseline is 3. The description adds meaningful parameter context by explaining the claim_token lifecycle ('Filing without an account returns a claim_token; pass it back later') and by instructing that context should reference Pipeworx tools/packs rather than user prompts. This extra guidance lifts it above baseline.

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 'Tell the Pipeworx team something is broken, missing, or needs to exist' and enumerates feedback types (bug, feature/data_gap, praise), making the verb and resource explicit. It clearly distinguishes itself from sibling tools like ask_pipeworx and discover_tools by restricting scope to 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 gives explicit triggers: 'Use when a tool returns wrong/stale data (bug)... feature/data_gap... praise.' It also provides an explicit exclusion: if the tool came from a different MCP server, file it with that server instead. This is strong when/when-not guidance with alternatives.

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

All Traject Ecommerce 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
Disambiguation4/5

Most tools have distinct purposes, e.g., Amazon and Walmart tools are platform-specific. A few overlapping tools like ask_pipeworx, ask_pipeworx_grounded, and deep_research are differentiated by clear usage guidance, so an agent can disambiguate with reasonable effort.

Naming Consistency3/5

Tool names mix verbs and nouns with varying styles (e.g., ai_visibility_check, compare_entities, scan_competitor_ai_presence). There is no uniform pattern like verb_noun; some are descriptive phrases. The inconsistency is noticeable but not chaotic.

Tool Count2/5

36 tools is too many for a server named 'Traject Ecommerce', as many tools cover unrelated domains (Polymarket, npm packages, SEC filings). The scope is excessively broad, making the server feel like a general-purpose plugin rather than a focused ecommerce toolset.

Completeness2/5

For an ecommerce-focused server, it only covers Amazon and Walmart product/search/reviews, missing major platforms and backend operations. The broader tool set is detailed but not ecommerce-specific, leaving obvious gaps for the intended purpose.

Resources