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by io.github.getgapup

webhooks_manage

Manage HTTP webhook callbacks for async tools (T5/T6 batch flagships). Instead of polling every 5s, register a callback URL — Gapup posts the job result to your endpoint the moment it completes. Supported events: job.completed | job.failed | monitoring.alert | quota.threshold. Modes: register (add endpoint), list (view active webhooks), revoke (soft-delete), test (fire a test payload to verify your receiver), history (last 20 fires). Security: every delivery is signed with HMAC-SHA256 on the body — verify the X-Gapup-Signature header against sha256(secret, body).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo(register) HTTPS/HTTP endpoint that will receive POST callbacks. Must return 2xx within 10s.
modeYesregister — add a webhook endpoint. list — view your active webhooks. revoke — soft-delete a webhook by webhook_id. test — fire a test payload to verify the receiver is alive. history — last 20 delivery attempts for a webhook.
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
eventsNo(register, optional) Events to subscribe to. Defaults to all events if omitted.
secretNo(register, optional) A secret string used to sign deliveries with HMAC-SHA256. Store it safely — verify X-Gapup-Signature header on your receiver.
webhook_idNo(revoke / test / history) The webhook_id returned from register.
caller_hashNoOptional caller identity override. If omitted, uses the internal session hash.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses key behaviors: soft-delete for revoke, HMAC-SHA256 signature for security, test mode, and history of last 20 fires. Annotations are consistent (non-readonly, non-destructive).

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 concise, front-loads purpose, and efficiently lists modes, events, and security in a structured manner without unnecessary words.

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 tool with 7 parameters and multiple modes, the description covers behavior, security, events, and usage flow. The presence of an output schema further reduces the need to detail return values.

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%, and the description adds extra context (e.g., async for slow tools, security details, soft-delete). While schema already describes each parameter, the description integrates them into a coherent workflow.

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 it manages HTTP webhook callbacks for async tools, listing specific events and modes. It distinguishes itself from sibling tools by focusing on webhook callback management.

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 explains when to use webhooks ('Instead of polling every 5s') and details each mode (register, list, revoke, test, history). However, it could be more explicit about when not to use it, but the context is sufficient.

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

C2.8/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially in competitive intelligence, ESG, and risk assessment. For example, there are multiple tools for competitor analysis (competitive_deep_dive, competitor_intel, competitor_moves, etc.) with unclear boundaries. Agents would struggle to select the correct tool without deep understanding of subtle differences.

Naming Consistency2/5

Tool names are a mix of English and French, and follow no consistent pattern. Some use snake_case (e.g., abm_architect, action_plan_esg), while others are verb-focused (e.g., content_catalog, fx_rate). The lack of a uniform naming convention makes it hard for agents to predict tool names.

Tool Count1/5

With 271 tools, the server is excessively large. Even for a broad knowledge domain, this number of tools makes discovery and selection inefficient. Typical coherent servers have 3-15 tools; this has an order of magnitude more, indicating poor scoping.

Completeness3/5

The tool set covers many domains (compliance, finance, marketing, HR, etc.), but the coverage is uneven due to redundancy. Key areas have multiple overlapping tools, while some sub-domains may still have gaps. Overall, the surface is broad but not well-curated.

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