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codefmt

by dev.codefmt
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Format/lint JS, Python, HubL for automation platforms. Tools: format_code, format_json, ask_codefmt

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Status
Healthy
Uptime
100.0% over 82 days
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL
ChatGPT
–
Claude
–

TDQS

A3.8/5.0

Scored across 3 tools

Disambiguation4/5

The three tools cover clearly different surfaces: documentation Q&A (ask_codefmt), source formatting/linting for JS/Python/HubL (format_code), and JSON pretty-print/minify (format_json). The only mild overlap is between format_code and format_json, since JSON is technically code, but the descriptions clearly bound format_code to JS/Python/HubL and format_json to raw JSON documents with key-sorting and 64-bit number preservation.

Naming Consistency4/5

All three names follow a consistent verb_noun pattern (ask_codefmt, format_code, format_json), making the action obvious at a glance. The minor deviation is that ask_codefmt's noun is the product name rather than a resource, which is slightly less predictable than the format_* pair.

Tool Count4/5

Three focused tools is lean but appropriate for a narrow formatting/linting service, with no filler or redundant entries. It is on the sparse side, but each tool maps to a genuine capability rather than being artificially split.

Completeness3/5

Core paths are covered (Q&A, code formatting+linting, JSON formatting), but there are notable gaps: no way to configure style options (indent width, quote style, key sort for code), no lint-only invocation, and no explicit discovery of supported languages/platforms other than free-text Q&A. Agents can work around most of these, but the surface feels narrow for a formatter.

Available Tools

3 tools
ask_codefmtAsk codefmtA
Read-only
Inspect

Ask a natural-language question about codefmt: formatting and linting JavaScript, Python, and HubL for automation platforms (Zapier, n8n, Pipedream, Make, HubSpot). Returns a grounded answer drawn from codefmt's own content with cited source URLs and a confidence score (0-1, how much of the question the answer covers, weighted toward its rarer terms); off-topic or too-weakly-matched questions are refused rather than guessed.

NameRequiredDescriptionDefault
queryYesThe natural-language question about codefmt.

Output Schema

NameRequiredDescription
answerYesThe grounded answer, or the refusal text.
resultsYesRanked matching entries.
sourcesYesCited source URLs.
confidenceNoHow much of the question the answer covers, weighted toward its rarer terms.

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses return behavior (grounded answer with cited source URLs), the meaning and scale of the confidence score (0-1, weighting toward rarer terms), and the refusal policy for weak matches. That is exactly the behavioral context an agent needs and cannot get from the annotation or schema.

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?

It is a single dense paragraph with the core purpose front-loaded, followed by domain scope, return behavior, and refusal policy. Every sentence carries information, though the heavy parenthetical listing makes it slightly more crowded than necessary.

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 one-parameter Q&A tool, the description covers domain, expected input, return shape, confidence semantics, and failure behavior. Even though an output schema exists (so return values needn't be explained), the added explanation of the confidence score is genuinely helpful and nothing material is missing.

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?

There is a single required parameter with 100% schema description coverage, so the schema already documents "query" fully. The description reinforces that the query must be natural-language and about codefmt, but adds no format, length, or syntax detail beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ("Ask a natural-language question about codefmt") and scopes the domain precisely (formatting/linting JS, Python, HubL for Zapier, n8n, Pipedream, Make, HubSpot). It is clearly distinct from format_code and format_json by the verb alone, but it never names or contrasts those siblings explicitly.

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?

It gives clear context for when the tool applies (NL questions about codefmt's subject matter) and a when-not rule ("off-topic or too-weakly-matched questions are refused rather than guessed"). It does not, however, tell the agent when to prefer this over the sibling formatting tools.

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

format_codeFormat code for automation platformsA
Read-only
Inspect

Format and lint JavaScript, Python, or HubL code for Zapier, n8n, Pipedream, Make, or HubSpot. Wraps the source in each platform's runtime shell before formatting so top-level await, bare return, and injected globals don't break the formatter. Returns formatted code plus lint diagnostics.

NameRequiredDescriptionDefault
codeYesSource code to format (≤50KB).
languageNoDefaults to javascript. typescript parses TypeScript on pipedream and reads as javascript elsewhere. zapier, n8n, pipedream, make, and hubspot support python; hubl does not.
platformYesTarget automation platform.

Output Schema

NameRequiredDescription
errorYesWhy the format failed, or null on success.
diagnosticsYesLint findings with line and column.
formatted_codeNoThe formatted source. Absent when the input was refused.
diagnostics_frameNoWhether diagnostic positions refer to the submitted code or the formatted code.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, so safety is covered. The description adds non-obvious behavioral context: the source is wrapped in each platform's runtime shell before formatting to handle top-level await, bare return, and injected globals, and that output includes lint diagnostics. It does not mention size limits (only in schema) or how severe/format of diagnostics appear.

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?

Three tight sentences: purpose first, the non-obvious wrapping behavior second, output third. No filler.

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?

Given a simple 3-param read-only tool with 100% schema coverage and an output schema, the description covers the critical non-obvious behavior (platform wrapping) and the return of diagnostics. An output schema exists, so return-format details needn't be explained. Only minor gaps in error/limit behavior keep it from 5.

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 semantic context by enumerating the supported languages and platform targets that map to the parameters, reinforcing the parameter constraints even though the schema already documents them in detail.

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?

States specific verbs (format and lint) and resources (JavaScript/Python/HubL code), names the target platforms, and clearly distinguishes itself from siblings format_json and ask_codefmt by outputting transformed code rather than answering questions.

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?

Clearly implies when to use it: before deploying code into Zapier, n8n, Pipedream, Make, or HubSpot. Platform-specific edge cases (hubl lacks Python support) are covered in the schema rather than the description. No explicit exclusion vs. ask_codefmt or format_json, so not a 5.

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

format_jsonFormat a JSON documentA
Read-only
Inspect

Format (pretty-print or minify) a JSON document, optionally sorting object keys. Number literals are preserved exactly (64-bit IDs safe); parse errors report the exact line and column.

NameRequiredDescriptionDefault
jsonYesThe JSON text to format.
indentNoIndentation: '2' or '4' spaces, 'tab', or 'minify'. Defaults to '2'.
sort_keysNoSort object keys alphabetically. Defaults to false.

Output Schema

NameRequiredDescription
errorYes"line L, col C: message" on a parse error, or null.
formatted_jsonNoThe formatted document. Absent when the input was refused.

TDQS

A3.6/5.0
Behavior4/5

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

readOnlyHint=true already declares a safe read, but the description adds genuine value beyond annotations: lossless preservation of number literals (64-bit IDs safe) and precise line/column error reporting. These are non-obvious behavioral traits that materially affect how an agent trusts and calls the tool.

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 dense sentences, front-loaded with the core operation and then the two edge-case guarantees. No filler; every clause carries distinct information.

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?

With an output schema present and 100% parameter coverage, the description need not explain returns. It covers the operation, options, numeric fidelity, and error reporting, so it is nearly complete; the only real gap is the missing sibling/usage guidance.

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 json, indent, and sort_keys fully. The description echoes pretty-print/minify and optional key sorting but adds no syntax or format detail beyond the schema, which is the expected baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (format/pretty-print/minify) and resource (JSON document), so an agent immediately knows the operation. It does not, however, name or distinguish itself from the siblings format_code or ask_codefmt, leaving the JSON-vs-other-language split implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use, when-not-to-use, or alternative routing despite two sibling tools (format_code, ask_codefmt) that plausibly overlap. The agent must infer that this is the JSON-specific formatter on its own.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool update
    • Changedformat_code2 fields changed
      • changedInput schema / properties / language / description
        Previous value: -"Defaults to javascript. zapier, n8n, pipedream, make, and hubspot support python; hubl does not."New value: +"Defaults to javascript. typescript parses TypeScript on pipedream and reads as javascript elsewhere. zapier, n8n, pipedream, make, and hubspot support python; hubl does not."
      • changedInput schema / properties / language / enum
        Previous value: -[
-  "javascript",
-  "python"
-]New value: +[
+  "javascript",
+  "typescript",
+  "python"
+]
  2. 1 tool update
    • Changedask_codefmt2 fields changed
      • addedOutput schema / properties / results / items / properties
        Added value: +{
+  "label": {
+    "type": "string"
+  },
+  "score": {
+    "type": "number"
+  },
+  "source": {
+    "type": "string"
+  }
+}
      • addedOutput schema / properties / results / items / required
        Added value: +[
+  "label",
+  "source",
+  "score"
+]
  3. 3 tool updates
    • Changedask_codefmt1 field changed
      • changedOutput schema / (root)
        Previous value: -nullNew value: +{
+  "properties": {
+    "answer": {
+      "description": "The grounded answer, or the refusal text.",
+      "type": "string"
+    },
+    "confidence": {
+      "description": "How much of the question the answer covers, weighted toward its rarer terms.",
+      "maximum": 1,
+      "minimum": 0,
+      "type": "number"
+    },
+    "results": {
+      "description": "Ranked matching entries.",
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "sources": {
+      "description": "Cited source URLs.",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "answer",
+    "sources",
+    "results"
+  ],
+  "type": "object"
+}
    • Changedformat_code1 field changed
      • changedOutput schema / (root)
        Previous value: -nullNew value: +{
+  "properties": {
+    "diagnostics": {
+      "description": "Lint findings with line and column.",
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "diagnostics_frame": {
+      "description": "Whether diagnostic positions refer to the submitted code or the formatted code.",
+      "enum": [
+        "input",
+        "output"
+      ],
+      "type": "string"
+    },
+    "error": {
+      "description": "Why the format failed, or null on success.",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "formatted_code": {
+      "description": "The formatted source. Absent when the input was refused.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "diagnostics",
+    "error"
+  ],
+  "type": "object"
+}
    • Changedformat_json1 field changed
      • changedOutput schema / (root)
        Previous value: -nullNew value: +{
+  "properties": {
+    "error": {
+      "description": "\"line L, col C: message\" on a parse error, or null.",
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "formatted_json": {
+      "description": "The formatted document. Absent when the input was refused.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "error"
+  ],
+  "type": "object"
+}
  4. 3 tool updates
    • First observedask_codefmt
    • First observedformat_code
    • First observedformat_json

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