IA-QA — 152 QA & Dev Tools for AI Agents

secret_scan

Read-onlyIdempotent

Scan text or code for leaked secrets: API keys (AWS, GCP, Azure, OpenAI, Anthropic, Stripe, GitHub, GitLab, Slack, Twilio, SendGrid, HuggingFace), Slack / Teams / Discord webhook URLs, private keys, JWTs, database connection strings, Bearer and Basic auth headers, and hard-coded values assigned to password/secret/token names (a value read at run time — Cypress.env(), os.getenv() — is not flagged). Returns findings with type, severity, line and a redacted preview. Regex-based, no network.

Input Schema

Name	Required	Description	Default
`input`	Yes	Text to scan — or an array of texts / {id, text} for a batch (one result each, worst gate on top).
`types`	No	Comma-separated families (default all): aws, gcp, azure, openai, anthropic, huggingface, github, gitlab, stripe, slack, teams, discord, cookie, twilio, sendgrid, jwt, private_key, connection_string, bearer, basic_auth, generic, or pattern names. An unknown value is rejected, never a silent "clean".

Output Schema

Name	Required	Description	Default
`summary`	No
`findings`	No
`risk_level`	No
`input_lines`	No
`scanned_types`	No
`secrets_found`	No
`findings_count`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedOct 31, 2026

addedInput schema / examples

Added value: +[
+  {
+    "input": "redis://cache:6379"
+  }
+]

changedInput schema / properties / input / description

Previous value: -"Text or code to scan for secrets"New value: +"Text to scan — or an array of texts / {id, text} for a batch (one result each, worst gate on top)."

changedInput schema / properties / input / type

Previous value: -"string"New value: +[
+  "string",
+  "array"
+]

changedInput schema / properties / types / description

Previous value: -"Comma-separated families to scan (default: all): aws, gcp, azure, openai, anthropic, huggingface, github, gitlab, stripe, slack, twilio, sendgrid, jwt, private_key, connection_string, bearer, basic_auth, generic. Individual pattern names (e.g. \"aws_access_key\", \"github_fine\") are also accepted. An unknown value is rejected with an error — a scoped scan never silently returns \"clean\"."New value: +"Comma-separated families (default all): aws, gcp, azure, openai, anthropic, huggingface, github, gitlab, stripe, slack, teams, discord, cookie, twilio, sendgrid, jwt, private_key, connection_string, bearer, basic_auth, generic, or pattern names. An unknown value is rejected, never a silent \"clean\"."

Changed2 schema fields changedAug 19, 2026

changedInput schema / properties / types / description

Previous value: -"Comma-separated types to scan (default: all). Options: aws, gcp, azure, openai, anthropic, stripe, github, gitlab, slack, twilio, sendgrid, huggingface, jwt, private_key, connection_string, bearer, basic_auth"New value: +"Comma-separated families to scan (default: all): aws, gcp, azure, openai, anthropic, huggingface, github, gitlab, stripe, slack, twilio, sendgrid, jwt, private_key, connection_string, bearer, basic_auth, generic. Individual pattern names (e.g. \"aws_access_key\", \"github_fine\") are also accepted. An unknown value is rejected with an error — a scoped scan never silently returns \"clean\"."

addedOutput schema / properties / scanned_types
```
Added value: +{}
```

Changed1 schema field changedJun 21, 2026

addedOutput schema / properties

Added value: +{
+  "findings": {},
+  "findings_count": {
+    "type": "number"
+  },
+  "input_lines": {
+    "type": "number"
+  },
+  "risk_level": {},
+  "secrets_found": {},
+  "summary": {
+    "type": "string"
+  }
+}

Changed1 schema field changedJun 10, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "type": "object"
+}

First observedMay 26, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds real value beyond that: 'Regex-based, no network' discloses the detection mechanism and its false-positive implications, and it explains that findings are returned with type, severity, line and a redacted preview, plus that runtime-read values are not flagged.

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?

Purpose is front-loaded in the first clause, followed by the detection inventory and two short closing sentences on output and mechanism. The long vendor enumeration is dense but each item earns its place by telling the agent what will be caught.

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, the description needn't document return values, and it still summarizes the finding shape. It covers input, mechanism, and an important exclusion, but omits how this differs from the sibling 'detect_secrets', which is the one thing an agent still needs.

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% and both parameters are documented in the schema, including the batch form and the comma-separated 'types' families, so the baseline of 3 applies. The description's enumeration of secret families loosely reinforces the 'types' parameter but adds no syntax or default behavior beyond what the schema already states.

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 opens with a specific verb and resource ('Scan text or code for leaked secrets') and enumerates the exact secret families detected, so an agent knows precisely what the tool produces. It does not, however, differentiate itself from the near-identical sibling 'detect_secrets', leaving the agent to guess which of the two to pick.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: the tool is for scanning text/code for secrets, and the parenthetical about run-time reads (Cypress.env(), os.getenv()) clarifies a boundary condition. There is no explicit when-to-use/when-not guidance and no mention of the competing 'detect_secrets' or 'redact_pii' siblings.

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

All IA-QA — 152 QA & Dev Tools for AI Agents tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.