This PR refactors authentication. It centralizes token resolution into a new AuthResolver class and removes the --token-source flag.
Scanned 9/2/2026
Install to Claude Code
npx -y skills add microsoft/apm --skill fixtures --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Fixtures?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/microsoft-fixtures-4921a0c0)More formats (shields.io, HTML) on the badges page.
# Auth refactor
This PR refactors authentication. It centralizes token resolution
into a new AuthResolver class and removes the --token-source flag.
## What changed
- Added a new file src/apm_cli/auth/resolver.py with the
AuthResolver class.
- Updated src/apm_cli/auth/__init__.py to export AuthResolver.
- Updated src/apm_cli/cli.py to use AuthResolver for all token
lookups and removed the --token-source flag.
- Updated src/apm_cli/integration/git.py to delegate to
AuthResolver and dropped the GITHUB_APM_PAT fallback.
- Added unit tests in tests/unit/auth/test_resolver.py.
- Updated CHANGELOG.md.
## Why
The previous code had token resolution logic scattered across
multiple modules. This was fragile and led to bugs. Centralizing
it makes the code cleaner and easier to maintain. This is a
significantly enhanced approach to authentication.
## Testing
I ran the tests and they passed. The audit also passed.
## Notes
This is a breaking change because the --token-source flag is
removed.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!
Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...
Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.
**Complete production-ready guide for Google Gemini embeddings API** This skill provides comprehensive coverage of the `gemini-embedding-001` model for generating text embeddings, including SDK usage, REST API patterns, batch processing, RAG integration with Cloudflare Vectorize, and advanced use cases like semantic search and document clustering. ---
Interview, source-challenge, verify, save, and ADR-gate fuzzy coding requests into Codex-ready implementation specs. Use when a feature, bugfix, refactor, migration, repo-wide change, or architecture task needs user-verified requirements, source-backed decisions, durable architecture decisions, acceptance criteria, validation commands, rollout notes, saved spec/ADR files, and a Codex execution prompt. Do not use when already fully specified or when the user wants direct implementation now.
Use when a repo needs CodeGraph plus ast-grep for Codex MCP setup, exploration, impact analysis, structural search, or safe refactor planning.