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Diagnose a PayRam setup (one call)

payram_doctor

Staged, read-only health diagnosis: server reachability -> merchant API key -> admin JWT -> payment readiness (wallets + listener workers). Returns ranked likely causes with exact fix commands for the first failing stage. Run this FIRST when anything PayRam-related fails.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
apiKeyNoMerchant API key (per-project). Defaults to PAYRAM_API_KEY. Obtain headlessly: ./setup_payram_agents.sh ensure-api-key
baseUrlNoPayRam server base URL. Defaults to PAYRAM_BASE_URL. The installer publishes on port 80 (http://localhost), not :8080.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
healthyYes
findingsYes
nextStepsYes
failedStageYesFirst failing stage: reachability | api-key | jwt | readiness; null when healthy
likelyCausesYesRanked causes for the first failing stage

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden. It explicitly states 'read-only' and explains the staged execution and the returns of fix commands for the first failing stage, giving clear stop conditions. It omits details about potential network calls or runtime, but the read-only marker is a key safety disclosure.

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?

The description is three concise sentences with no waste. Each sentence provides distinct value: the staged pipeline, the output behavior, and the usage instruction.

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 complex diagnostic tool, the description captures the staged flow, the output type, the stopping condition, and the read-only nature. With an output schema present, the description adequately covers all necessary context for correct invocation.

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 coverage is 100%, with detailed parameter descriptions that include defaults and operational nuances (e.g., port 80 vs 8080). The description itself adds no extra parameter context, so the baseline 3 is appropriate.

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 clearly states the tool diagnoses a PayRam setup via a specific staged pipeline (server reachability, merchant API key, admin JWT, payment readiness). It also distinguishes itself from sibling tools by positioning as the first-line check for any PayRam failure.

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?

Provides an explicit when-to-use instruction: 'Run this FIRST when anything PayRam-related fails.' This is strong guidance, but it does not explicitly name alternative tools or when not to use it, so it falls short of full coverage.

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

B3.3/5.0
Disambiguation3/5

Many tools have distinct targets, but there is notable overlap in diagnostics (check_node_sync, check_payment_readiness, payram_doctor, test_payram_connection) and a large cluster of snippet generators for different languages that could be confused. The descriptions help, but several tools appear to serve the same underlying purpose.

Naming Consistency3/5

Snake_case is used consistently, but verb prefixes vary unpredictably: check_, generate_, get_, list_, lookup_, search_, snippet_, test_, restart_, etc. Similar actions use different verbs (lookup_payment vs search_payments vs get_payment_summary; generate_payment_route_snippet vs snippet_express_payment_route), making the naming pattern less predictable.

Tool Count2/5

With 52 tools, the set is significantly over-scoped for a developer assistance server. Many tools could be consolidated (e.g., a single snippet generator with language parameters, or unified health diagnostics), and the count introduces unnecessary complexity for agents.

Completeness3/5

The surface covers payments (create, lookup, search, summary), diagnostics, docs, and many integration snippets, but lacks direct payout creation (only snippet generators), no refund or wallet creation. These are notable gaps for a payments platform server, though the snippet tools and diagnostics mitigate some dead ends.

Resources