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 mamahoos/dot-files --skill k6-trend-analysisgit clone --depth 1 https://github.com/mamahoos/dot-filesWrote 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/mamahoos/dot-files/k6-trend-analysis)<a href="https://agentmods.dev/skills/mamahoos/dot-files/k6-trend-analysis"><img src="https://agentmods.dev/badge/skills/mamahoos/dot-files/k6-trend-analysis/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/mamahoos/dot-files/k6-trend-analysis"><img src="https://agentmods.dev/badge/skills/mamahoos/dot-files/k6-trend-analysis.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 | $0.00005 | $0.04672 |
| Opus 5 | $0.00003 | $0.02336 |
| Sonnet 5 | $0.00001 | $0.00934 |
| Haiku 4.5 | $0.00001 | $0.00467 |
Grade A, and why
k6-trend-analysis 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 6d 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.
This is a copy
98% identical to k6-trend-analysis — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 421 lines — stays where its author put it; the contents beside it link to each section on GitHub.
k6 Trend Analysis
Analyze metric trends across multiple runs of a Grafana Cloud k6 test to catch degradation early -- before thresholds breach and alerts fire. A P95 at 380ms against a 500ms threshold is "green" today, but if it was 250ms a month ago, something is quietly degrading; this skill surfaces that drift and recommends action.
What this skill does NOT do
- Deep-dive into a single run's failure: load
k6-cloud-investigate-test - Edit scripts or apply threshold changes: load
k6-test-maintenance - Create new test scripts: use the appropriate test creation workflow
- Query service-side metrics directly: this skill hands off to
debug-with-grafanawhen observability correlation is needed
Dependencies
This skill delegates all GCk6 API mechanics to k6-manage. Read it before
executing any API call -- it covers auth, path construction (the doubled
cloud/cloud/ prefix), pagination with @nextLink, the spill envelope, and
metric query syntax. Do not duplicate that knowledge here.
Tools used: gcx (via k6-manage patterns).
Workflow
Follow these steps in order. Present findings at the end -- do not apply changes.
Step 1: Identify the test
The user provides one of:
- A GCk6 URL (extract the load test ID from the path)
- A test ID directly
- A test name (search via
gcx k6 tests listor the v6 API)
Confirm the test exists by fetching its metadata. Record the id, name,
project_id, and created timestamp. You will need the load test ID (not a
run ID) for the multi-run metric endpoints.
Step 2: Determine the analysis window
Default to last 30 days. Adjust if:
- The user requests a specific window
- The test has very few runs (<5 in 30 days) -- widen the window and note this
- The test runs very frequently (hundreds of runs in 30 days) -- consider sampling or narrowing. Ask the user if the volume is extreme (>200 runs)
State the window explicitly: "Analyzing runs from {start_date} to {end_date}."
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.
- 6d ago First seen · 421 lines · 5 tokens per session scan A 964d6203e064
k6-trend-analysis is a skill published in the GitHub repository mamahoos/dot-files (4 stars, last pushed today), licensed MIT. It adds 5 tokens to every session and 4,672 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to k6-trend-analysis, differing in 1 line, and is treated as a copy.
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