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Jubstaaa

standup-mr

by Jubstaaa
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

get_standup_data

Retrieve merge-request standup data from GitLab/GitHub: JSON snapshot of today's events, MR states, pending reviews, and pipeline error blockers. Call at day start to write a standup note.

Instructions

Collect merge-request-based standup data from GitLab or GitHub. Returns one JSON object: today, previousDays[] with the events of each, todayEvents[], myMrs[] bucketed ready / blocked / draft / stale, reviews[] waiting on you, and blockers[] carrying the error lines read out of each failed pipeline job log.

Call it once at the start of a working day, to write a standup note. It is a snapshot, not a search API: it cannot fetch one named merge request, reach further back than the previous working day, or filter by project.

Read-only, and credentials never come from an argument — they come from the environment or a logged-in gh / glab session. A rejected token, a refused resource or a rate limit fails the call with the host's own message, after two retries on transient server errors. A blocker whose diagnosis could not be fetched is still returned, with job: "unknown", so a red pipeline is never silently dropped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hostNoSelf-hosted host, without a scheme, e.g. gitlab.example.com or github.example.com. Required for GitLab, which has no default host; optional for GitHub, which defaults to github.com. A recognisable host also settles `provider` on its own, so the two are rarely both needed.
langNoLanguage for the date labels inside the returned JSON: en (default) or tr. It relabels dates and nothing else — no field is translated, and the standup note itself is written by the caller, in whatever language they are speaking.
providerNoWhich provider to read. Omit to auto-detect, in this order: a recognisable host, STANDUP_PROVIDER, a GITHUB_*/GITLAB_* environment pair, then whichever of the gh / glab CLIs is logged in. Pass it when both are configured — ambiguity fails the call rather than being guessed at.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changedv0.4.1
    • changedInput schema / properties / host / description
      Previous value: -"Self-hosted host, without a scheme, e.g. gitlab.example.com or github.example.com. GitHub defaults to github.com; GitLab has no default, so self-hosted GitLab needs this or GITLAB_HOST."New value: +"Self-hosted host, without a scheme, e.g. gitlab.example.com or github.example.com. Required for GitLab, which has no default host; optional for GitHub, which defaults to github.com. A recognisable host also settles `provider` on its own, so the two are rarely both needed."
    • changedInput schema / properties / lang / description
      Previous value: -"Language for the date labels inside the returned JSON. Defaults to en. Only the labels change — the standup note itself is written by the caller."New value: +"Language for the date labels inside the returned JSON: en (default) or tr. It relabels dates and nothing else — no field is translated, and the standup note itself is written by the caller, in whatever language they are speaking."
    • changedInput schema / properties / provider / description
      Previous value: -"Which provider to read. Omit to auto-detect, in this order: a recognisable host, STANDUP_PROVIDER, a GITHUB_*/GITLAB_* environment pair, then whichever of the gh / glab CLIs is logged in."New value: +"Which provider to read. Omit to auto-detect, in this order: a recognisable host, STANDUP_PROVIDER, a GITHUB_*/GITLAB_* environment pair, then whichever of the gh / glab CLIs is logged in. Pass it when both are configured — ambiguity fails the call rather than being guessed at."
  2. Changed3 schema fields changedv0.1.1
    • addedInput schema / properties / host
      Added value: +{
+  "description": "Self-hosted host, without a scheme, e.g. gitlab.example.com or github.example.com. GitHub defaults to github.com; GitLab has no default, so self-hosted GitLab needs this or GITLAB_HOST.",
+  "type": "string"
+}
    • addedInput schema / properties / lang
      Added value: +{
+  "description": "Language for the date labels inside the returned JSON. Defaults to en. Only the labels change — the standup note itself is written by the caller.",
+  "enum": [
+    "en",
+    "tr"
+  ],
+  "type": "string"
+}
    • addedInput schema / properties / provider
      Added value: +{
+  "description": "Which provider to read. Omit to auto-detect, in this order: a recognisable host, STANDUP_PROVIDER, a GITHUB_*/GITLAB_* environment pair, then whichever of the gh / glab CLIs is logged in.",
+  "enum": [
+    "github",
+    "gitlab"
+  ],
+  "type": "string"
+}
  3. First observedv0.1.0

TDQS

A4.9/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so thoroughly. It discloses read-only nature, credential sourcing from environment or logged-in sessions, retry behavior on transient errors, error message propagation, and the handling of undiagnosable blockers with 'job: "unknown"'. These are non-obvious behavioral traits critical for an agent to invoke safely.

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 detailed but every sentence serves a purpose: it front-loads the return structure, then states usage, then safety and error behavior. There is no filler or redundancy; the length is justified by the complexity of the tool's behavior.

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?

Given the absence of an output schema and sibling tools, the description compensates by fully specifying the return object's top-level fields, usage timing, limitations, authentication, and error cases. An agent has all necessary information to correctly decide when and how to call this tool.

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?

The input schema already provides 100% coverage with detailed descriptions for all three parameters, including defaults and auto-detection rules. The description adds minor complementary context, such as the purpose of 'lang' and the relationship between host and provider, but the schema does the heavy lifting. A score of 4 reflects the schema's richness and the description's reinforcing value.

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's function with a specific verb ('Collect') and resource ('merge-request-based standup data from GitLab or GitHub'), and outlines the exact shape of the returned JSON object. This is a precise, action-oriented description that leaves no ambiguity about what the tool does.

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

Usage Guidelines5/5

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

Explicitly states when to use: 'Call it once at the start of a working day, to write a standup note.' It also defines exclusions: 'It is a snapshot, not a search API: it cannot fetch one named merge request, reach further back than the previous working day, or filter by project.' This provides clear context and boundaries for usage.

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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