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Ctrlanmol

scamcheck

by Ctrlanmol

Open an evidence case

open_case

Create a local evidence case for a suspected scam and optionally attach analyzed text; evidence is SHA-256 hashed at collection for later export or complaint drafting.

Instructions

Open a local evidence case and optionally attach the analysed text. Evidence is SHA-256 hashed at collection time and stored under ~/.scamcheck (mode 0700). Use this when a user wants to report a scam or preserve proof; the case can later be exported with the CLI (--case-export) or turned into a complaint draft (--report).

Input Schema

NameRequiredDescriptionDefault
notesNoOpening notes.
titleYesShort case title.
currencyNoe.g. INR, USD.
scam_typeNoe.g. upi, bank, crypto, job, romance, sextortion.
loss_amountNoReported loss, if any.
evidence_textNoMessage text to attach as hashed evidence.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.13.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that evidence is SHA-256 hashed at collection time, persisted to ~/.scamcheck with mode 0700, and is local-only. It omits whether re-opening/duplicate cases are possible, what identifier or path is returned, and any failure modes (disk, permissions).

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 sentences, zero filler: the first covers what happens and where data lands, the second covers when to use it and what the artifact is good for. Storage and hashing are front-loaded before the usage guidance.

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?

A six-parameter mutation tool with no annotations and no output schema — the description supplies storage location, permissions, integrity mechanism (hashing), and downstream export paths, which is most of what an agent needs. The notable remaining gap is what the call returns (case ID or path) so the agent can reference the case later.

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 all six parameters are already documented; baseline is 3. The description adds only marginal meaning by indicating evidence_text is optional and gets hashed, and says nothing about currency, loss_amount, scam_type, or notes.

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 and resource — 'Open a local evidence case' — plus the optional attachment of analysed text, which is clearly distinct from the read-only checking siblings (check_number, check_message, check_url). It doesn't explicitly name a sibling as the alternative path, so the differentiation is inferred rather than stated.

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?

'Use this when a user wants to report a scam or preserve proof' gives an explicit trigger condition, and the follow-on paths (--case-export, --report) tell the agent what the case is for downstream. No when-not guidance or comparison to the check_* tools, but the usage context is unambiguous.

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