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.
npx skills add ashish7802/awesome-api-skills --skill lokigit clone --depth 1 https://github.com/ashish7802/awesome-api-skillsWrote 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/skills/ashish7802/awesome-api-skills/loki)<a href="https://agentmods.dev/skills/ashish7802/awesome-api-skills/loki"><img src="https://agentmods.dev/badge/skills/ashish7802/awesome-api-skills/loki.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 18 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
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 | $0.00000 | $0.00534 |
| Opus 5 | $0.00000 | $0.00267 |
| Sonnet 5 | $0.00000 | $0.00107 |
| Haiku 4.5 | $0.00000 | $0.00053 |
Grade A, and why
loki 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 8d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loki Skill
Like Prometheus, but for logs.
Ecosystem Graph
graph LR
loki["Loki"]
loki -- "depends on" --> grafana
loki -- "works well with" --> prometheus
Quick Start
Loki aggregates logs but, unlike Elasticsearch, it only indexes metadata labels rather than the full text of the log. This makes it insanely cheap and fast to operate.
docker run -d -p 3100:3100 grafana/loki
Production Patterns
LogQL vs Full Text
Do not expect to do complex full-text fuzzy searching natively. Loki forces you to filter by labels first (e.g., {app="backend", env="prod"}), and then it aggressively scans the chunks of text that match those labels.
Architecture & Scaling
Promtail
Loki requires an agent to ship logs. Promtail is the official agent. Deploy Promtail as a DaemonSet in Kubernetes to automatically scrape all pod stdout logs and forward them to the centralized Loki instance.
Error Recovery
Loki will actively reject logs if they are sent out of chronological order (a common issue in highly distributed systems). Ensure you configure unordered_writes: true in your Loki configuration to mitigate this.
Security Notes
Do not inject dynamic, unbounded user data (like session IDs or IPs) as Loki Labels. This causes Cardinality explosions, crashing the system. Log the dynamic data in the text payload, and only label static data (app name, region, environment).
Relationships
Prerequisites: grafana
Works Well With: prometheus
References
Why use this skill
Use this when your agent works with loki — structured patterns beat pasted docs and prevent common hallucinations.
AI pitfalls
- Using outdated SDK or API versions from training data
- Inventing environment variable names
- Omitting error handling and retry logic
Production checklist
- Secrets in environment variables, not source code
- Error handling and logging in place
- Rate limits and timeouts configured
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 8d ago First seen · 62 lines · 0 tokens per session scan A 8f39491fcdc5
loki is a skill published in the GitHub repository ashish7802/awesome-api-skills (13 stars, last pushed 8d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 534 tokens. 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.
Other skills, from other repositories
ios-simulator
Verify and debug native, React Native, Expo, or Flutter apps on an iOS Simulator with agent-device. Use when an agent needs to launch an app, inspect its live UI, tap, type, scroll, validate a code change, collect failure evidence, or reproduce a workflow on an iPhone or iPad Simulator.
manage-skills
A maintenance workflow for checking whether project verification skills still cover the code and rules that changed during a session.
systematic-debugging
Structured debugging methodology — use before proposing fixes for any error or failure. Covers: code bugs, build errors, deploy failures, config conflicts, dependency issues, infra problems. Also use when previous fix attempts failed or root cause is unclear.
review-loop
Run the adversarial verification loop — implement, then hand the change to a fresh checker that did not write it, fix what it finds, and re-dispatch until APPROVE. Use before claiming any behavioural change is done, and on requests like "review loop", "adversarial review", "independent review", "get this verified"…
iii-error-handling
Handle iii engine and SDK errors across Node, Python, Rust, and browser workers. Use when interpreting error codes, retryability, RBAC denial, timeouts, handler failures, or SDK-specific exception surfaces.
debug
Systematic debugging with MCP integration, auto-invoke from qa-commit, Phase 7 Harden.