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 controlplane-com/ai-plugin --skill logql-observabilitygit clone --depth 1 https://github.com/controlplane-com/ai-pluginWrote 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/controlplane-com/ai-plugin/logql-observability)<a href="https://agentmods.dev/skills/controlplane-com/ai-plugin/logql-observability"><img src="https://agentmods.dev/badge/skills/controlplane-com/ai-plugin/logql-observability/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/skills/controlplane-com/ai-plugin/logql-observability"><img src="https://agentmods.dev/badge/skills/controlplane-com/ai-plugin/logql-observability.svg" alt="Reviewed on agentmods" width="80" 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 Memory Poisoning · line 108 Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
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 | $0.00053 | $0.02581 |
| Opus 5.5 | $0.00021 | $0.01032 |
| Sonnet 5.5 | $0.00011 | $0.00516 |
| Haiku 4.5 | $0.00005 | $0.00258 |
Grade A, and why
logql-observability 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 17d 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LogQL & Log Observability
Control Plane stores workload stdout/stderr in Loki and queries it with LogQL. The org is the Loki tenant — it comes from the endpoint path, so org is never a query label and queries cannot cross orgs. Reading logs requires the org-level readLogs permission, and the in-pod CPLN_TOKEN cannot authenticate to the logs endpoint — use a user or service-account token (see the workload skill). The recurring agent failure is passing a raw query to the MCP tool alongside structured params: a raw query replaces them entirely (the tool rejects the combination), so a raw query must embed every label itself.
Two ways to query
- MCP (primary for agents):
mcp__cpln__get_workload_logs— structured paramsgvc(required),workload,container,location,filter(literal substring, LogQL|=, not regex); windowsince(default1h) orfrom/to(ISO 8601,frominclusive,toexclusive);limit(default 30, max 999, single request —truncated: truemeans narrow the window or filter harder);order(oldest_firstdefault, ornewest_first). For regex, parsers, or thereplica/stream/versionlabels, pass a rawquery(max 500 chars) instead of the structured selectors. - CLI:
cpln logs '<LOGQL>'— interactive debugging (live--tail), scripts, CI.
# Defaults: --since 1h, --limit 30, --direction forward
cpln logs '{gvc="GVC", workload="WORKLOAD"}' --org ORG
cpln logs '{gvc="GVC", workload="WORKLOAD"} |= "error"' --limit 100
cpln logs '{gvc="GVC", workload="WORKLOAD", container="main"}' --since 7d
cpln logs '{gvc="GVC", workload="WORKLOAD"}' --tail # live follow; the server ends a tail session after 30m
cpln logs '{gvc="GVC", workload="WORKLOAD"}' \
--from 2026-06-01T00:00:00Z --to 2026-06-02T00:00:00Z # ISO 8601 or relative (7d, now-1M); from inclusive, to exclusive
cpln logs '{gvc="GVC", workload="WORKLOAD"} |= "error"' --since 24h --limit 0 # 0 = unlimited, auto-paginates
cpln logs '{gvc="GVC", workload="WORKLOAD"}' -o jsonl # one JSON object per line; -o raw = bare lines
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.
- 17d ago Changed · -24 lines 57a66a5fbb04
- 1mo ago First seen · 148 lines · 53 tokens per session scan A b81a2a8a8c86
logql-observability is a skill published in the GitHub repository controlplane-com/ai-plugin (11 stars, last pushed 3d ago), licensed MIT. It adds 53 tokens to every session and 2,581 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.
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