logging

Guidance for adding and reviewing application logs, which are records of what software is doing and when. It covers log levels, structured formats, YAML configuration, backends, rotation, and information that should not be recorded.

In plain words
What is it for?
Use it when adding logging, checking existing output, selecting levels such as INFO or ERROR, configuring logging in YAML, or planning local and production log handling.
Why use it?
It helps teams choose useful messages and severity levels without exposing sensitive data or producing logs that are difficult to operate. It also accounts for different needs in prototypes, internal tools, and production systems.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/andr-ca/agentharness/logging
Any agent
npx skills add andr-ca/agentharness --skill logging
Clone the repo
git clone --depth 1 https://github.com/andr-ca/agentharness

Made for: Claude Code, Codex.

Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 809 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00051 $0.00809
Opus 5 $0.00026 $0.00404
Sonnet 5 $0.00010 $0.00162
Haiku 4.5 $0.00005 $0.00081

Measured 2d ago against content hash 8c5715037128, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

logging 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 2d 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.

.claude/skills/logging/SKILL.md · 98 lines

How it starts

The opening of the file, as written. The whole thing — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Logging

This skill is self-contained for day-to-day use. Deeper reference (needs the full harness checkout): patterns/logging/LOGGING_STANDARDS.md (full mandate and config schema), patterns/logging/logging.yaml.example (tested YAML template), patterns/logging/config_loader.py (Python reference implementation with 99% test coverage).

When this applies

Full structured logging with YAML config, multiple backends, and rotation is required at Production tier. Prototypes: print()/console.log() is fine. Internal tools: structured logging recommended, single-backend acceptable. Check the project's rigor tier first.

Log levels — pick the right one

Level Use for
TRACE High-frequency per-call details; disabled in production by default
DEBUG Developer diagnostic info; disabled in production by default
INFO Normal operational events (startup, request completed)
WARNING Something unexpected but recoverable; worth investigating
ERROR A real failure that the system couldn't recover from
CRITICAL The process must stop or data is corrupted

Rule of thumb: if you'd page someone at 3am, it's ERROR or CRITICAL.

Structured logging: message + fields, never string interpolation

# WRONG: unstructured — can't query or filter by user_id or duration
logger.info(f"Request completed for user {user_id} in {duration}ms")

# RIGHT: message is a static label; context is in structured fields
logger.info("request.completed", user_id=user_id, duration_ms=duration)
// Node/pino/winston equivalent
logger.info({ userId, durationMs }, 'request.completed');

What NOT to log

Never log: passwords, tokens, API keys, full credit card numbers, SSNs, session IDs, or any data under a PII/GDPR policy. Redact or omit before logging. If logging usefulness and secrecy conflict, redact. Do not log the secret "for completeness."

# WRONG: logs the raw token
logger.info("auth.token_issued", token=issued_token)

# RIGHT: log only what's safe to expose
logger.info("auth.token_issued", user_id=user_id, expires_at=exp)

Read the full file on GitHub · 98 lines

Changes

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.

  1. 2d ago First seen · 98 lines · 51 tokens per session scan A 8c5715037128

Subscribe to this mod's changes

logging is a skill published in the GitHub repository andr-ca/agentharness (1 stars, last pushed 2d ago), licensed MIT. It adds 51 tokens to every session and 809 once invoked, about $0.0003 per session on Opus 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 2026-08-31.

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