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Energy Charts

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

A4.9/5.0
Behavior5/5

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

Annotations are all false, so the description carries the full burden. It reveals rate-limiting ('Rate-limited to 5 per identifier per day'), cost ('Free; doesn't count against your tool-call quota'), and the claim_token flow (returned when filing without an account, pass it back later to read status). This exceeds what annotations provide.

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?

Though long, every sentence earns its place: scope, use cases, exclusions, token mechanics, rate limits, and cost. The structure front-loads the purpose and then systematically covers usage, limitations, and follow-up, making it dense but efficient.

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 4-parameter tool with no output schema, the description fully covers the lifecycle: when to use, when not to use, what to include, rate limits, and how to retrieve results via claim_token. It is complete for an agent to decide and invoke the tool correctly.

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 covers 100% of parameters, so baseline is 3. The description adds value beyond schema by explaining the claim_token round-trip pattern and how to use it ('pass it back later as pipeworx_feedback({claim_token:"pwfb_…"})') and by advising users to describe issues in terms of Pipeworx tools rather than pasting prompts.

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 and resource: 'Tell the Pipeworx team something is broken, missing, or needs to exist.' It clearly distinguishes the tool's scope with 'ONLY for tools served by this Pipeworx connection,' differentiating it from sibling research/data tools.

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 explicit when-to-use scenarios (bug, feature/data_gap, praise) and a clear when-not-to-use rule: if the tool came from a different MCP server, file it there instead. Also offers a practical heuristic for ambiguity ('Not sure? Pipeworx tool names are the ones this connection lists.').

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_grounded, and deep_research, which all perform similar data retrieval. The multiple Polymarket tools also overlap in focus, making it unclear which to use for a given task.

Naming Consistency2/5

Tool names are inconsistent: some use 'ask_', 'polymarket_', 'pipeworx_', while others like 'electricity_price', 'installed_power', and 'remember' follow no coherent pattern. Conventions are mixed and unpredictable.

Tool Count2/5

With 35 tools, the server is over-scoped for an 'Energy Charts' purpose. Only 5-6 tools are directly energy-related; the rest are a miscellany of data services, prediction markets, and memory functions, which is excessive and unfocused.

Completeness2/5

The server lacks essential energy analysis tools like forecast, emission factors, or capacity utilization, yet includes many unrelated tools (e.g., betting, memory). This creates significant gaps for the stated domain.

Resources