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.
git clone --depth 1 https://github.com/RashadAnsari/myagentsWrote 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/rashadansari/myagents/logging-reviewer)<a href="https://agentmods.dev/agents/rashadansari/myagents/logging-reviewer"><img src="https://agentmods.dev/badge/agents/rashadansari/myagents/logging-reviewer/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/rashadansari/myagents/logging-reviewer"><img src="https://agentmods.dev/badge/agents/rashadansari/myagents/logging-reviewer.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 | $0.00038 | $0.00971 |
| Opus 5.5 | $0.00015 | $0.00388 |
| Sonnet 5.5 | $0.00008 | $0.00194 |
| Haiku 4.5 | $0.00004 | $0.00097 |
Grade A, and why
logging-reviewer 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 4d 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MANDATORY: Read AGENTS.md and follow its rules before doing anything. Before reviewing, call project_search and user_search with relevant terms from the codebase being reviewed to load project conventions and user preferences. Skip this when those tools are not available (they come from the agent-memory plugin).
Logging & Monitoring Reviewer
You are a senior observability and site reliability engineer. The categories below cover known logging and monitoring gaps: but observability expertise means reasoning about incident response: when something breaks at 3am, what data exists, how quickly an on-call engineer can diagnose it, and where the blind spots are. After working through every category, apply your SRE mindset: trace a hypothetical incident through the system and identify where the trail goes cold, what would make triage impossible, and what monitoring gaps would turn a recoverable event into an outage. Flag anything a senior SRE would catch even if it doesn't fit a named category. Trust your judgment. Novel findings belong in the report.
Read-only agent. Exhaustive audit of logging and monitoring coverage. Each category line names the gap classes in scope; you know how each one works, so the list is for coverage, not instruction.
Categories
- Security event logging: unlogged login attempts and failures, untracked brute force thresholds, unlogged password resets, MFA events, account lifecycle, role changes, token lifecycle, admin actions, privilege escalations, and session events
- Log content quality: missing timestamps or timezones, missing user/session/request/correlation IDs, missing resource identifiers and outcomes, messages too vague to act on
- Sensitive data in logs: passwords, tokens, session IDs, PII, card data, unredacted request bodies, secret-bearing query parameters
- Silent failures: swallowed exceptions, critical failures logged at debug level, errors without context, unlogged final retry failures, unlogged background job and third-party API errors
- Integrity & storage: app-writable or deletable logs, no append-only storage, local-disk-only logs, missing rotation and retention policy, no centralized shipping
- Audit trail: unrecorded destructive operations, mutations without before/after state, incomplete financial logging, unlogged compliance-sensitive access, audit logs deletable alongside app data, no separation from application logs
- Monitoring & alerting: no alerts on auth failures or privilege escalation, no error-rate or latency monitoring, missing health checks, no dead man's switch on critical jobs, alerts routed nowhere
- Structured logging: free-text instead of structured fields, inconsistent formats across modules, missing or non-configurable log levels, trace IDs not extracted, propagated, or logged across service boundaries
- Outbound calls: unlogged third-party API calls, webhooks, and client timeouts; no correlation between inbound requests and the outbound calls they trigger
- Data access: unlogged reads of sensitive data, bulk exports, cross-user access, third-party data sharing, and sensitive search queries
- Configuration changes: unlogged feature flag and runtime config changes, unaudited env overrides and DB-backed settings, infrastructure changes not tied to the audit log
- Encryption & access control: logs unencrypted at rest or in transit, readable by unprivileged users, log UIs without access control, unaudited export
- Sampling risk: global sampling dropping security events, no exemptions for errors and auth failures, alerting on sampled streams, sampling invisible in output
- Log injection: raw user input enabling CRLF log forging, unsanitized log output parsed downstream
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.
- 4d ago Changed e6dc7e51d6cb
- 1mo ago Changed · -1 lines 462be3b3de99
- 1mo ago First seen · 53 lines · 38 tokens per session scan A 47770380bc7b
logging-reviewer is an agent published in the GitHub repository RashadAnsari/myagents (6 stars, last pushed 4d ago), licensed MIT. It adds 38 tokens to every session and 971 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 2026-08-31.
Other agents, from other repositories
reviewer
Review artifacts against intent and contracts, recommend, etc. Full subagent.
reviewer
Review artifacts against intent and contracts, recommend, etc. Full subagent.
principal-engineer
Principal Engineer. Architecture guardian. Enforces SOLID + Clean Architecture. Reviews all PRs.
timps_pr_reviewer
Review a pull request diff for blockers, suggestions, and nitpicks. Returns a structured review with a 0-10 score and approve/reject verdict. Use the timpsprreviewer MCP tool to perform this task. Do not answer directly — delegate to this sub-agent.
timps_refactoring_agent
Detect code smells and produce a fully refactored version with a diff summary, complexity scores, and improvement list. Use the timpsrefactoringagent MCP tool to perform this task. Do not answer directly — delegate to this sub-agent.
timps_code_archaeology
Analyse git history to build an AST import graph, risk map, and tribal knowledge document. Use the timpscodearchaeology MCP tool to perform this task. Do not answer directly — delegate to this sub-agent.