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AppFactory

by gbatistuta0
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Python
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GitHub Issue Create

github_issue_create
Destructive

Creates a GitHub issue for postponed work, using role and next/later labels; defaults to dry-run planning and requires approval for live creation.

Instructions

Open a GitHub issue for postponed work (needs human approval unless dry_run).

Use when: parking work with a role label plus next or later. dry_run=true (default) returns the exact command. No-op (n/a) when the github_issues run option is off. Returns: {ok, url/command, dry_run} or an approval_required refusal.

Input Schema

NameRequiredDescriptionDefault
bodyYesIssue body with what / why / done-when sections.
repoYesGitHub repository as 'owner/name', e.g. 'octocat/my-app'.
titleYesIssue title in imperative form, e.g. 'Add offer paywall analytics'.
labelsYesIssue labels: one role label (ios, backend, store, lead, founder) plus next or later.
app_dirNoApp directory; when given, the github_issues run option is read from its spec.
dry_runNoIf true (default) nothing is changed or sent and the exact plan/command is returned; false performs the live action.
approval_idNoApproval id from a previous approval_required refusal; omit on the first call. The human approves out-of-band with `appfactory approve <id>`, then call again with the same arguments and this id.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changedv0.1.5
    • addedInput schema / properties / app_dir / description
      Added value: +"App directory; when given, the github_issues run option is read from its spec."
    • addedInput schema / properties / approval_id / description
      Added value: +"Approval id from a previous approval_required refusal; omit on the first call. The human approves out-of-band with `appfactory approve <id>`, then call again with the same arguments and this id."
    • addedInput schema / properties / body / description
      Added value: +"Issue body with what / why / done-when sections."
    • addedInput schema / properties / dry_run / description
      Added value: +"If true (default) nothing is changed or sent and the exact plan/command is returned; false performs the live action."
    • addedInput schema / properties / labels / description
      Added value: +"Issue labels: one role label (ios, backend, store, lead, founder) plus next or later."
    • addedInput schema / properties / repo / description
      Added value: +"GitHub repository as 'owner/name', e.g. 'octocat/my-app'."
    • addedInput schema / properties / title / description
      Added value: +"Issue title in imperative form, e.g. 'Add offer paywall analytics'."
  2. First observedv0.1.1

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the destructive/openWorld annotations, it discloses the human-approval gate, the dry_run default behavior (returns the exact command, changes nothing), the no-op condition, and the possible approval_required refusal. That is rich operational context an agent cannot get from annotations alone.

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?

Three short labeled lines (what, when, returns) with the mutation/approval caveat front-loaded in the first clause. No sentence is 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 an output schema present and rich annotations, the description covers the remaining gaps an agent needs: the approval workflow, dry_run default, no-op condition, and refusal outcome. Nothing essential for correct invocation is missing.

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 the schema already documents all seven parameters including dry_run and approval_id. The description reinforces the label convention ('role label plus next or later') but adds no new syntax or format detail, so the baseline 3 applies.

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?

States a specific verb and resource ('Open a GitHub issue') plus the intended scope ('for postponed work'), which cleanly separates it from github_create_repo and github_push in the sibling list. An agent can identify the tool without opening the schema.

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 explicit when-to-use ('parking work with a role label plus next or later') and a when-not/no-op condition ('when the github_issues run option is off'). It stops short of naming alternative siblings to route to, but the activation conditions are unambiguous.

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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