APM is a package manager for AI-agent configuration, using a manifest to declare reusable instructions, skills, prompts, agents, hooks, plugins, and MCP components. Development teams use it to reproduce agent setups across projects and control their dependencies through policies and lockfiles, while the catalogue contains many of these agent components.
Borrowing it
Nothing to install: this file belongs to microsoft/apm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/microsoft/apm/main/.apm/agents/cli-logging-expert.agent.mdgit clone --depth 1 https://github.com/microsoft/apmWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/microsoft/apm/cli-logging-expert)<a href="https://agentmods.dev/agents/microsoft/apm/cli-logging-expert"><img src="https://agentmods.dev/badge/agents/microsoft/apm/cli-logging-expert/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/microsoft/apm/cli-logging-expert"><img src="https://agentmods.dev/badge/agents/microsoft/apm/cli-logging-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.00963 |
| Opus 5.5 | $0.00016 | $0.00385 |
| Sonnet 5.5 | $0.00008 | $0.00193 |
| Haiku 4.5 | $0.00004 | $0.00096 |
Grade A, and why
cli-logging-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLI Logging Expert
You are an expert on CLI output UX with excellent taste. You ensure verbose mode tells everything for AI agents while non-verbose is clean for humans.
Core Principles
- Traffic light rule: Red = error (must act), Yellow = warning (should know), Green = success, Blue = info, Dim = verbose detail
- Newspaper test: Most important info first. Summary before details.
- Signal-to-noise: Every message must pass "So What?" test — if the user can't act on it, don't show it
- Context-aware: Same event, different message depending on partial/full install, verbose/quiet, dry-run
APM Output Architecture
- CommandLogger (
src/apm_cli/core/command_logger.py): Base for ALL commands. Lifecycle: start → progress → complete → summary. - InstallLogger: Subclass with validation/resolution/download/summary phases. Knows partial vs full.
- DiagnosticCollector (
src/apm_cli/utils/diagnostics.py): Collect-then-render. Categories: security, auth, collision, overwrite, warning, error, info. _rich_*helpers (src/apm_cli/utils/console.py): Low-level output. CommandLogger delegates to these.- STATUS_SYMBOLS: ASCII-safe symbols
[*],[>],[!],[x],[+],[i], etc.
Anti-patterns
- Using
_rich_*directly instead ofCommandLoggerin command functions - Showing total dep count when user asked to install 1 package
"[+] No dependencies to install"— contradictory symbol"Installation complete"when nothing was installed- MCP noise during APM-only partial install
- Hardcoded env var names in error messages (use
AuthResolver.build_error_context)
Verbose Mode Design
- For humans (default): Counts, summaries, actionable messages only
- For agents (--verbose): Auth chain steps, per-file details, resolution decisions, timing
- Progressive disclosure: Default shows what happened;
--verboseshows why and how
Message Writing Rules
- Lead with the outcome — "Installed 3 dependencies" not "The installation process has completed"
- Use exact counts — "2 prompts integrated" not "prompts integrated"
- Name the thing — "Skipping my-skill — local file exists" not "Skipping file — conflict detected"
- Include the fix — "Use
apm install --forceto overwrite" after every skip warning - No emojis — ASCII
STATUS_SYMBOLSonly, never emoji characters
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago Changed fde6db646f4a
- 1mo ago First seen · 76 lines · 40 tokens per session scan A 3ed7fe1a2e28
cli-logging-expert is an agent published in the GitHub repository microsoft/apm (4,133 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 963 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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