Skip to main content
Glama

AI SENSE Free Public Tools

by com.aisenseapi
OverviewDiscussionsAdmin

Verify a hash

verify_hash
Read-onlyIdempotent

Check that text matches a hash. Name the algorithm when you know it. Without it the algorithm follows from the hash: 8, 32, 40, 64 or 128 hex characters mean CRC32, MD5, SHA-1, SHA-256 or SHA-512, and an integer means CRC32 in decimal; whirlpool, sha3_256, sha3_512, blake2b and blake3 share those lengths and must be named. For argon2id, bcrypt and scrypt the hash is the salted string those algorithms answered; the cost is read from it and must be within what this service produces. Answers match and algorithm, with computed for digests and params for password hashes. No API key, no account and no sign up: call it directly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
hashYesThe hash to compare against.
algorithmNoOptional for the first five, required for the rest.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / algorithm / enum
      Previous value: -[
-  "md5",
-  "sha1",
-  "sha256",
-  "sha512",
-  "crc32",
-  "whirlpool",
-  "sha3_256",
-  "sha3_512",
-  "blake2b"
-]New value: +[
+  "md5",
+  "sha1",
+  "sha256",
+  "sha512",
+  "crc32",
+  "whirlpool",
+  "sha3_256",
+  "sha3_512",
+  "blake2b",
+  "blake3",
+  "argon2id",
+  "bcrypt",
+  "scrypt"
+]
  2. Changed1 schema field changed
    • addedInput schema / properties / algorithm
      Added value: +{
+  "description": "Optional for the first five, required for the rest.",
+  "enum": [
+    "md5",
+    "sha1",
+    "sha256",
+    "sha512",
+    "crc32",
+    "whirlpool",
+    "sha3_256",
+    "sha3_512",
+    "blake2b"
+  ],
+  "type": "string"
+}
  3. Added

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, it discloses the auth posture ("No API key, no account and no sign up"), the response contents (match, algorithm, computed, params), and a constraint on password hashes (cost must be "within what this service produces"). That is substantial behavior beyond the structured fields.

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 and every sentence carries information, but the inference rules are packed into a dense run-on block that takes effort to parse. Slightly longer than ideal, though nothing is truly wasted.

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?

With no output schema, the description supplies the return shape itself, covers auth requirements, and explains the exception cases (salted password hashes, shared-length algorithms). An agent has everything needed to call it correctly without further inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 67%, and the description compensates with the algorithm inference map (8/32/40/64/128 hex chars and decimal integer), the caveat that whirlpool/sha3/blake variants share lengths and must be named, and how the hash is interpreted for argon2id/bcrypt/scrypt. This is meaning well beyond the terse schema 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?

"Check that text matches a hash" states a specific verb (check/verify) and resource (hash of text), which is immediately distinguishable from the sibling hash_data. The description never leaves ambiguity about what the tool returns: a match verdict plus algorithm.

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 conditional guidance for the optional algorithm parameter ("Name the algorithm when you know it"; otherwise infer from hash length) and notes no auth/setup is required. It stops short of routing agents between this and the sibling hash_data, which is the one usage gap.

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

All AI SENSE Free Public Tools toolsInspect
Try in Browser
Shareable, User-Owned Context BackendPeople, applications, and agents read, write, and coordinate together in one context lake. Reach it over MCP, a CLI, a Python SDK, or REST.fulcradynamics.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources