marin: Skill for Claude Code

.agents/skills/query-finelog/SKILL.md

query-finelog is a skill for Claude Code, Codex from marin-community/marin. It costs 58 tokens per session (1,103 once invoked), scanned A, original, Apache-2.0.

A procedure for querying Finelog, a logging and telemetry system used to inspect Iris tasks, workers, profiles, training, model serving, and cluster forwarding. It requires checking available namespaces and schemas before writing SQL queries.

In plain words
What is it for?
It helps investigate resource use, compare central and regional clusters, calculate counter changes, diagnose query performance, and report time windows and data limitations.
Why use it?
It prevents incorrect queries and misleading conclusions caused by guessed columns, different counter types, or missing data between clusters.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is marin-community/marin's own configuration. It tells Claude Code and Codex how to work on marin itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything marin configures →

About the project

Marin is an open-source research program, software platform, and community for developing foundation models such as large language models. Researchers use it for data preparation, tokenization, pretraining, posttraining, evaluation, and related experiments, including work on audio-text, DNA, and protein models. The catalogue entries are add-ons that support workflows around Marin.

marin-community/marin · 4,074 stars · on GitHub · marin.community

Reuse

Borrowing it

Nothing to install: this file belongs to marin-community/marin. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/marin-community/marin/main/.agents/skills/query-finelog/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/marin-community/marin

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for query-finelog

README.md
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Your own site
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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.

agentmods 80×15 button for query-finelog

Your own site · 80×15
<a href="https://agentmods.dev/skills/marin-community/marin/query-finelog"><img src="https://agentmods.dev/badge/skills/marin-community/marin/query-finelog.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,103 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 5.1 $0.00058 $0.01103
Opus 5.5 $0.00023 $0.00441
Sonnet 5.5 $0.00012 $0.00221
Haiku 4.5 $0.00006 $0.00110

Measured 2mo ago against content hash 52875188ba5b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

query-finelog 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 2mo 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.

.agents/skills/query-finelog/SKILL.md · 118 lines

How it starts

The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Query Finelog

Read lib/finelog/OPS.md for access and query behavior. Read lib/iris/OPS.md under Stats Namespaces for Iris namespace meanings.

Discover before querying; do not assert remembered columns:

uv run finelog namespaces <deployment>
uv run finelog schema <deployment> <namespace>
uv run finelog query <deployment> --format table <<'SQL'
<bounded SQL using schema-confirmed columns>
SQL

finelog query reads SQL from stdin when the positional SQL argument is omitted.

Use marin for the federated view and a regional deployment for peer-local truth or recent rows that may not have forwarded. Preserve cluster and full process/label identity until after per-series delta calculations.

Bound the native time key. Keep telemetry_v1.timestamp_ms predicates numeric. Treat current snapshots as values, imported Prometheus counters as cumulative snapshots with LAG and reset handling, and native Rigging counters as deltas to SUM directly.

Never reset or change a shared namespace during diagnosis. Return the deployment, namespace, time window, query, series semantics, and any forwarding or retention caveat.

Examples

Confirm every schema before adapting an example. Angle-bracket values are placeholders.

Iris task memory by half-hour

Adapted from Echo wiki 230. The dashboard task ID includes the final task index. Select or group by attempt_id after retries.

SELECT date_bin(INTERVAL '30 minutes', ts,
                TIMESTAMP '1970-01-01 00:00:00') AS bucket_start_utc,
       count(*) AS samples,
       round(min(memory_mb) / 1024.0, 1) AS min_gib,
       round(median(memory_mb) / 1024.0, 1) AS median_gib,
       round(max(memory_mb) / 1024.0, 1) AS max_gib,
       round(max(memory_peak_mb) / 1024.0, 1) AS attempt_peak_gib
FROM "iris.task"
WHERE task_id = '/user/job/task'
  AND attempt_id = 0
GROUP BY bucket_start_utc
ORDER BY bucket_start_utc

memory_mb is sampled current memory; memory_peak_mb is the attempt's cumulative peak. Values are MiB despite the names. count(*) exposes partial buckets and gaps. Query the regional deployment if recent hub rows appear incomplete.

Read the full file on GitHub · 118 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. 2mo ago First seen · 118 lines · 58 tokens per session scan A 52875188ba5b

Subscribe to this mod's changes

query-finelog is a skill published in the GitHub repository marin-community/marin (4,074 stars, last pushed today), licensed Apache-2.0. It adds 58 tokens to every session and 1,103 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.

Related

query-finelog compared with skills from other repositories

query-finelog next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
query-finelogmarin-community/marinSkill4.1ktodayApache-2.0A58Claude Code, Codex
imagegenopenai/codexSkill133kyesterdayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99kyesterdayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79k4d agoMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill313k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143ktodayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143ktodayMITA103Claude Code