Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/dynatrace-oss/dynatrace-snowflake-observability-agentnpx agentmods add skills/dynatrace-oss/dynatrace-snowflake-observability-agent/dynatrace-dashboardWrote 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/dynatrace-oss/dynatrace-snowflake-observability-agent/dynatrace-dashboard)<a href="https://agentmods.dev/skills/dynatrace-oss/dynatrace-snowflake-observability-agent/dynatrace-dashboard"><img src="https://agentmods.dev/badge/skills/dynatrace-oss/dynatrace-snowflake-observability-agent/dynatrace-dashboard/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/dynatrace-oss/dynatrace-snowflake-observability-agent/dynatrace-dashboard"><img src="https://agentmods.dev/badge/skills/dynatrace-oss/dynatrace-snowflake-observability-agent/dynatrace-dashboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00017 | $0.09197 |
| Opus 5 | $0.00009 | $0.04598 |
| Sonnet 5 | $0.00003 | $0.01839 |
| Haiku 4.5 | $0.00002 | $0.00920 |
Grade A, and why
dynatrace-dashboard 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 10d 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 — 881 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Dynatrace Dashboard Creation and Deployment
Use this skill to create, update, convert, and deploy Dynatrace dashboards for DSOA telemetry visualisation.
File Locations
| Artefact | Path |
|---|---|
| Dashboard YAML source | docs/dashboards/<dashboard-name>/<dashboard-name>.yml |
| Dashboard readme | docs/dashboards/<dashboard-name>/readme.md |
| Screenshot placeholder | docs/dashboards/<dashboard-name>/img/.gitkeep |
| Dashboards index | docs/dashboards/README.md |
| Workflow YAML source | docs/workflows/<workflow-name>/<workflow-name>.yml |
| Workflow readme | docs/workflows/<workflow-name>/readme.md |
Dashboard names use a descriptive slug, not necessarily the plugin name,
since dashboards may span multiple plugins (e.g. snowpipes-monitoring,
tasks-pipelines, budgets-finops).
Metric / Attribute Reference
Before writing any DQL query, consult the plugin's semantic dictionary:
src/dtagent/plugins/<plugin-name>.config/instruments-def.yml
This is the authoritative source for:
- Metric keys (e.g.
snowflake.pipe.files.pending) - Dimensions (e.g.
snowflake.pipe.name,db.namespace) - Log/event attributes
- Telemetry types (metrics, logs, events, bizevents, spans)
All DSOA telemetry carries these standard dimensions on every record:
db.system == "snowflake"deployment.environment— Snowflake account identifierdsoa.run.plugin— plugin name (e.g."snowpipes")dsoa.run.context— context name (e.g."snowpipes_copy_history")
DQL Rules (Lessons Learned)
These rules come from real debugging sessions — follow them strictly:
- Determine the actual telemetry type before writing any DQL.
DSOA plugins can emit logs, events, metrics, or bizevents — and the plugin
source is the only authoritative answer. Before writing a tile query, check
the plugin's
_log_entries()call insrc/dtagent/plugins/<plugin>.py:- No
report_timestamp_events=Trueand noevent_payload_prepare→ logs only → usefetch logs report_timestamp_events=True→ timestamp events in addition to logs → usefetch eventsfor event tilesreport_all_as_events=True→ all rows as events → usefetch events- Metrics in
instruments-def.ymlwith a metric key → usetimeseries
- No
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.
- 10d ago First seen · 881 lines · 17 tokens per session scan A ff594e50ef71
dynatrace-dashboard is a skill published in the GitHub repository dynatrace-oss/dynatrace-snowflake-observability-agent (10 stars, last pushed 8d ago), licensed MIT. It adds 17 tokens to every session and 9,197 once invoked, about $0.0001 per session on Opus 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 2026-09-02.
Other skills, from other repositories
cocoreview
CocoReview — structured code review with six-severity findings vocabulary, progressive disclosure architecture, and universal anti-pattern baseline. Invoked via $review [file] [--complexity] [--security] [--architecture] [--language ].
pod-init
Initialize CocoPlus project bundle in the current directory. Creates .cocoplus/ directory structure, copies all templates, initializes AGENTS.md, project.md, flow.json, and creates the initial git commit. Run this once per project before using any other CocoPlus command.
spec
Enter the Spec phase of CocoBrew. Guides the developer through structured requirements capture: goal, success criteria, constraints, personas involved, data sources, and deliverables. Writes spec.md to .cocoplus/lifecycle/ and creates a git commit.
discuss
Run a structured decision-capture dialogue before $plan — locks implementation choices (model, evaluation methodology, accuracy threshold, scope boundaries) into discuss.md to prevent silent decision drift during planning. Supports --red-team flag for adversarial post-PASS challenge session.
cocoharvest
Decompose an approved plan into parallel workstreams, assign specialist personas, classify stages as HITL or AFK (CocoLens), generate flow.json stages with checkpoints and dual-file state, and create per-stage prompt files. Includes adaptive parallelism, stall detection, shell identity injection, and consecutive…
pull
Distill large context files (evaluation artifacts, schema dumps, query result sets, analysis outputs) into LLM-optimized dense form or human-readable narrative (--human). Default output is machine-dense; --human produces a prose summary for stakeholder consumption.