doc-tspec-autopilot_skill

This skill automatically generates and validates TSPEC from SPEC documents for UTEST, ITEST, STEST, and FTEST with TASKS-Ready scoring.
  • Python

9

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

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npx veilstrat add skill vladm3105/aidoc-flow-framework --skill doc-tspec-autopilot

  • SKILL.md25.1 KB

Overview

This skill automates generation and review of TSPEC test specifications from SPEC documents, producing UTEST, ITEST, STEST, and FTEST artifacts with TASKS-Ready scoring. It detects input type (SPEC or TSPEC), generates missing TSPEC suites in a nested folder layout, validates TASKS-Ready compliance, and runs an iterative review-and-fix cycle until quality targets are met. The pipeline supports both generate and review modes and emits structured markdown reports and traceability updates.

How this skill works

The autopilot parses the input identifier (SPEC-NN or TSPEC-NN) to decide whether to generate a TSPEC or run a review. For generation it extracts methods, interfaces, and data models from SPEC, plans coverage, and creates four test-type files per TSPEC (UTEST/ITEST/STEST/FTEST) with traceability tags and element IDs. It then validates TASKS-Ready scoring, applies auto-fixes where possible, and runs a review/fix loop using the doc-tspec-reviewer and doc-tspec-fixer skills until the target score or iteration limit is reached.

When to use it

  • You have SPEC documents and need complete TSPEC suites with test types and traceability.
  • You want to validate existing TSPEC directories and produce a TASKS-Ready quality report.
  • You need automated conversion of SPEC coverage into UTEST/ITEST/STEST/FTEST artifacts.
  • You require an iterative review-and-fix workflow to reach a TASKS-Ready threshold.
  • You need standardized element IDs and cumulative traceability tags across test specs.

Best practices

  • Provide SPEC identifiers in the format SPEC-NN so the autopilot can detect upstream inputs.
  • Keep SPEC documents well-structured (methods, interfaces, data models) to improve extraction accuracy.
  • Run validation with strict TASKS-Ready thresholds enabled when preparing for downstream TASKS generation.
  • Maintain the nested TSPEC folder convention (TSPEC-NN_{slug}/) so reports and traceability updates land correctly.
  • Limit parallel execution to the configured max_parallel to avoid resource contention.

Example use cases

  • Generate TSPEC-05 from SPEC-05 when no TSPEC folder exists, producing four test-type files and a coverage matrix.
  • Review TSPEC-01 to get a TASKS-Ready score breakdown and an R_review_report_v001.md with actionable fixes.
  • Run an automated fix cycle: detect legacy element IDs, convert them to TSPEC.NN.TT.SS, regenerate the coverage matrix, and revalidate.
  • Batch-process multiple SPEC inputs (SPEC-01,SPEC-02) to create or review corresponding TSPEC suites with iterative fixes.
  • Produce a final TASKS-Ready report and update the project traceability matrix before TASKS generation.

FAQ

Use identifiers like SPEC-NN for generation or TSPEC-NN for review; directory inputs for bulk review are also supported.

What is the TASKS-Ready target score?

Default target is 90%; this is configurable in the skill configuration under scoring.tasks_ready_min.

Can the autopilot auto-fix issues?

Yes. Auto-fix applies to common problems (missing test type files, legacy IDs, broken links, coverage matrix) and is governed by max fix iterations.

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doc-tspec-autopilot skill by vladm3105/aidoc-flow-framework | VeilStrat