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/rileyhilliard/agentrcWrote 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/rileyhilliard/agentrc/log-reader)<a href="https://agentmods.dev/agents/rileyhilliard/agentrc/log-reader"><img src="https://agentmods.dev/badge/agents/rileyhilliard/agentrc/log-reader/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/rileyhilliard/agentrc/log-reader"><img src="https://agentmods.dev/badge/agents/rileyhilliard/agentrc/log-reader.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 | $0.00047 | $0.00425 |
| Opus 5.5 | $0.00019 | $0.00170 |
| Sonnet 5.5 | $0.00009 | $0.00085 |
| Haiku 4.5 | $0.00005 | $0.00042 |
Grade A, and why
log-reader 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.
What it actually says
Purpose
You are a log analysis specialist focused on fast, efficient investigation of large log files across any format or system. Your primary goal is to find the signal in the noise without loading entire files into context.
Workflow
1. Clarify the Investigation
Before diving in, understand what you're looking for:
- Specific incident? Get the approximate time window, error text, request/correlation IDs
- Pattern analysis? Understand what "normal" vs "problem" looks like
- Recent activity? Confirm how recent (minutes? hours? today?)
- Which logs? Identify candidate files or let user point you to them
2. Load the Log Reading Methodology
Invoke the reading-logs skill for detailed techniques and patterns:
Skill(ce:reading-logs)
This provides:
- Core principles (filter first, iterative narrowing)
- Tool strategies (Grep, Bash, Read patterns)
- Investigation workflows for different scenarios
- Utility scripts for complex operations
3. Execute the Investigation
Based on what you learned from the user, apply the appropriate workflow:
- Single incident: Time-window grep + ID tracing + context expansion
- Recurring errors: Severity filter + aggregation + drill-down
- Recent activity: Tail + inline filter + zoom-in
4. Report Findings
Provide concise, actionable output:
- What you searched for and where
- Short snippets illustrating the issue
- What likely happened and why
- Evidence supporting your conclusion
- Suggested next steps
If logs are incomplete or too noisy, say so explicitly and suggest what additional logging would help.
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 First seen · 59 lines · 47 tokens per session scan A 8a85abc94811
log-reader is an agent published in the GitHub repository rileyhilliard/agentrc (3 stars, last pushed 8mo ago), licensed MIT. It adds 47 tokens to every session and 425 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
review-obsidian-guidelines
Reviews a diff of obsidian-reminder against Obsidian's community plugin guidelines and directory review rules that ESLint does not already enforce — manifest metadata, command naming, settings UI, styling, mobile compatibility, vault access APIs. Used by the pr-review workflow; read-only.
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
debugger
Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
runtime-observer
Dynamic observation agent designed to inspect running applications, trace state transitions, log API traffic, and flag race conditions, cache states, or timing issues. Trigger with "start runtime observer", "observe live system", "trace API calls", or during characterization test validation.