Agent skill

Greptimedb Perses Dashboard

by GreptimeTeam in GreptimeTeam/dashboard

Generate Perses dashboards or single panels for GreptimeDB. An agent skill from GreptimeTeam/dashboard.

Apache-2.0Auto-check passedDevOps & Cloud

Install Greptimedb Perses Dashboard

skills CLI
$ npx skills add GreptimeTeam/dashboard --skill greptimedb-perses-dashboard -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install GreptimeTeam/dashboard greptimedb-perses-dashboard --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/GreptimeTeam/dashboard.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/greptimedb-perses-dashboard .claude/skills/greptimedb-perses-dashboard && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
greptimedb-perses-dashboard
GitHub stars
111
Token cost
~3.9k tokens
SKILL.md length
1,309 words
Files
4 (incl. scripts)
Skills in repo
1
Repo updated
First seen
Licence
Apache-2.0

At a glance

Generate Perses dashboards or single panels for GreptimeDB. An agent skill from GreptimeTeam/dashboard.

  • Works in 7 steps: Clarify input → Choose data path → Discover data (MCP or HTTP) → …
  • The user asks to create
  • SKILL.md covers Datasource constraint (hard…, Data access (required), Live reference API and Workflow, plus 4 more sections
  • Runs Shell scripts from its folder; calls curl and node

What it does

Greptimedb Perses Dashboard is an agent skill from GreptimeTeam/dashboard. Generate Perses dashboards or single panels for GreptimeDB. Use when the user asks to create, generate, or scaffold a Perses dashboard or panel from table names, SQL/PromQL queries, natural-language prompts, or JSON paste into the Perses editor. Dashboard output is compatible with GET/POST /v1/dashboards; panel output is a paste-ready Panel object with kind Panel. Datasources are limited to promql-default (Prometheus) and sql-default (GreptimeDB) only. Reference GET /v1/dashboards for live metrics (SQL/PromQL)…

Its SKILL.md is about 3.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts (for example `catalog.md`, `reference.md` and `scripts/save-dashboard.sh`). Compatibility notes: Any Agent Skills or MCP-capable host (Cursor, Claude Desktop/Code, GitHub Copilot, Codex, Gemini CLI, custom agents, etc.); GreptimeDB Dashboard with Perses…

It sits in DevOps & Cloud, covering Monitoring and alerting, SQL and MCP servers. It works with Prometheus, SQL, Model Context Protocol and Vue.js. The repository describes itself as: GreptimeDB dashboard web application. The licence is Apache-2.0.

When your agent uses it

  • The user asks to create
  • Scaffold a Perses dashboard
  • Panel from table names
  • SQL/PromQL queries

Example prompts

  • “/greptimedb-perses-dashboard”

Requirements

  • A Bash shell
  • Compatibility (from SKILL.md): Any Agent Skills or MCP-capable host (Cursor, Claude Desktop/Code, GitHub Copilot, Codex, Gemini CLI, custom agents, etc.); GreptimeDB Dashboard with Perses; data via GreptimeDB MCP server or HTTP API

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Clarify input
  2. Choose data path
  3. Discover data (MCP or HTTP)
  4. Select panel type
  5. Generate JSON
  6. Validate queries
  7. Deliver

What it can do on your machine

Read from SKILL.md and the folder at commit 1f6e93e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • curl
    • node

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • modelcontextprotocol.io
    • perses.dev

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Any Agent Skills or MCP-capable host (Cursor, Claude Desktop/Code, GitHub Copilot, Codex, Gemini CLI, custom agents, etc.); GreptimeDB Dashboard with Perses; data via GreptimeDB MCP server or HTTP API

    From compatibility in the SKILL.md frontmatter.

Context cost

Greptimedb Perses Dashboard loads about 3.9k tokens when it runs. Until then it costs about 143 tokens; SKILL.md has 1,309 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~143
When it runs · the whole SKILL.md, loaded when a task matches
~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from GreptimeTeam/dashboard at commit 1f6e93e, republished under its Apache-2.0 licence (© GreptimeTeam). 1,309 words, ~3,945 tokens.

Download SKILL.mdSave it as .claude/skills/greptimedb-perses-dashboard/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
greptimedb-perses-dashboard
description
Generate Perses dashboards or single panels for GreptimeDB. Use when the user asks to create, generate, or scaffold a Perses dashboard or panel from table names, SQL/PromQL queries, natural-language prompts, or JSON paste into the Perses editor. Dashboard output is compatible with GET/POST /v1/dashboards; panel output is a paste-ready Panel object with kind Panel. Datasources are limited to promql-default (Prometheus) and sql-default (GreptimeDB) only. Reference GET /v1/dashboards for live metrics (SQL/PromQL), logs, and traces formats.
compatibility
Any Agent Skills or MCP-capable host (Cursor, Claude Desktop/Code, GitHub Copilot, Codex, Gemini CLI, custom agents, etc.); GreptimeDB Dashboard with Perses; data via GreptimeDB MCP server or HTTP API
license
Apache-2.0

Perses Dashboard Generator

Generate Perses Dashboard or single Panel JSON for the GreptimeDB Dashboard app.

Read first: catalog.md — panel shapes, JSON examples, live dashboard index.

Also: reference.md (schema, SQL/PromQL rules).

Output modes:

User intentOutput
dashboard / save to APIFull Dashboard JSON
panel / single panel / paste JSONSingle Panel object only (kind: "Panel")

Datasource constraint (hard rule)

Greptime Dashboard only supports two datasource plugins. Never use any other kind or name:

NamePlugin kindQuery plugins
promql-defaultPrometheusDatasourcePrometheusTimeSeriesQuery
sql-defaultGreptimeDBDatasourceGreptimeDBTimeSeriesQuery, GreptimeDBLogQuery, GreptimeDBTraceQuery

Forbidden: Loki, Tempo, Elasticsearch, InfluxDB, ${ds}, Grafana datasource variables, inline URLs, or any other datasource.

When migrating Grafana JSON, replace all datasource references with promql-default or sql-default.

Data access (required)

Before generating panels, discover real table/column names and dry-run queries. Use either path below — not both unless cross-checking.

PathWhen to useHost / connection
GreptimeDB MCP serverAny agent with MCP enabledHost/auth in the agent’s MCP server config; call health_check to verify
HTTP APINo MCP, shell/curl, CI, scripted agentsResolve GREPTIME_HOST (see reference.md — HTTP host)

Do not invent table/column names without discovery.

MCP (GreptimeDB MCP server)

The GreptimeDB MCP server is agent-agnostic — any host that implements the Model Context Protocol can use it (Cursor, Claude Desktop, Claude Code, VS Code Copilot, Codex, Gemini CLI, custom runners, etc.). The server name in config may vary (e.g. user-greptimedb, greptimedb); tool names below are what the server exposes.

ToolWhen to use
health_checkConfirm MCP can reach GreptimeDB before discovery
describe_tableColumn names, data_type, semantic_type
execute_sqlSample rows, dry-run SQL panel queries
query_rangeValidate PromQL metrics exist and return data
explain_queryDebug slow or failing SQL

MCP host/auth is not passed per tool call — it is set once in the agent’s MCP config (stdio command, env vars, or remote URL). If health_check fails, fix that MCP server entry or fall back to HTTP.

HTTP (no MCP)

Same operations via GreptimeDB HTTP API on {host}:

NeedEndpointExample
Probe connectionPOST {host}/v1/sqlSELECT 1
List dashboards (templates)GET {host}/v1/dashboards—
Table schemaPOST {host}/v1/sqlDESCRIBE TABLE public.my_table or information_schema.columns
Run SQLPOST {host}/v1/sqlPanel query with literals instead of ${__from}
PromQL rangeGET {host}/v1/prometheus/api/v1/query_rangequery, start, end, step
Save dashboardPOST {host}/v1/dashboards/{name}save-dashboard.sh

Confirm host (HTTP only) — resolve in order, stop when a probe succeeds:

  1. User-provided URL (e.g. https://greptime.example.com, http://127.0.0.1:4000)
  2. GREPTIME_HOST environment variable
  3. Local default: http://127.0.0.1:4000 (GreptimeDB HTTP API; matches config/vite.config.base.ts dev proxy target)
  4. Same origin as Dashboard UI — if the user runs Greptime Dashboard in dev, frontend /v1/* is proxied to 127.0.0.1:4000; direct curl still targets that backend unless deployed otherwise

Probe (replace host and auth as needed):

bash
HOST="${GREPTIME_HOST:-http://127.0.0.1:4000}"
curl -sS -o /dev/null -w "%{http_code}" -X POST "$HOST/v1/sql" \
  -H "Content-Type: application/x-www-form-urlencoded" \
  --data-urlencode "sql=SELECT 1"
# Expect HTTP 200

Auth headers for HTTP: GREPTIME_AUTH (Basic), GREPTIME_DB (x-greptime-db-name) — same as save-dashboard.sh. Full curl patterns: reference.md — HTTP API.

If discovery and HTTP both fail, use offline catalog.md shapes only and tell the user which host/MCP setting is missing.

Live reference API

Fetch existing dashboards before generating (match real query/panel shapes):

bash
curl -s "${GREPTIME_HOST:-http://127.0.0.1:4000}/v1/dashboards"
User asks forCopy patterns from dashboard
SQL metrics / tableGreptimeDB Perses Demo, test
PromQL / node exporterNode Exporter, test (panel prom)
Logslog
TracesTraces Demo
Mixed observabilityGreptimeDB Perses Demo + log + Traces Demo

See catalog.md for parsed panel JSON per modality.

Workflow

1. Clarify input

Identify one of:

  • Table name (schema.table or public.my_table)
  • Natural language goal ("monitor CPU", "temperature by location")
  • Existing SQL or PromQL query
  • Grafana JSON to migrate (use percli migrate, then tweak — see reference.md)
  • Multi-modal observability (metrics + logs + traces)
  • Single panel only (paste into Perses editor → Add panel → JSON)

Default to single panel when the user mentions: panel, single panel, paste JSON, add panel, import panel.

Default to full dashboard when the user mentions: dashboard, save dashboard, /v1/dashboards.

2. Choose data path

Follow the Greptime + Perses guide:

ScenarioPathDatasourceQuery plugin
Prometheus metrics, node_exporterPromQLpromql-defaultPrometheusTimeSeriesQuery
GreptimeDB tables, logs, traces, RANGE/ALIGNSQLsql-defaultGreptimeDBTimeSeriesQuery / GreptimeDBLogQuery / GreptimeDBTraceQuery
Grafana JSON providedMigrate firstMap to promql-default after migration—
3. Discover data (MCP or HTTP)

SQL path — MCP: describe_table + execute_sql … LIMIT 5. HTTP: DESCRIBE TABLE / information_schema + POST /v1/sql.

Identify:

  • Time column: use schema detection (below) — not column-name guessing
  • Time unit: read data_type for Nanosecond vs Millisecond — nanosecond columns (e.g. web_trace_demo.timestamp) must use to_timestamp_millis(col) AS ts in TimeSeriesChart / Table queries or the UI can hang/crash (reference.md — Timestamp precision)
  • Value columns: numeric fields for charts
  • Tag columns: dimensions for series grouping (host, loc, sensor_id)
  • Trace columns: trace_id, span_id, parent_span_id
  • Log columns: message, content, body, level

Time column (same as SQL Builder — src/components/sql-builder/index.vue, src/utils/table-normalizer.ts):

  1. From describe_table columns, keep those where data_type.toLowerCase().includes('timestamp')
  2. Prefer semantic_type === 'TIMESTAMP'
  3. Pick the first match in that preferred set; else the first timestamp data_type column
  4. If none → no time column; do not assume ts / greptime_timestamp by name

See reference.md — Time column detection.

PromQL path — MCP: query_range. HTTP: GET /v1/prometheus/api/v1/query_range (or labels API).

Show full SKILL.md (516 more words)Show less
4. Select panel type
ModalityChart pluginQuery wrapper kindQuery plugin
Metrics (SQL)TimeSeriesChart, StatChart, TableTimeSeriesQueryGreptimeDBTimeSeriesQuery
Metrics (PromQL)TimeSeriesChart, GaugeChart, StatChartTimeSeriesQueryPrometheusTimeSeriesQuery
LogsLogsTableLogQueryGreptimeDBLogQuery
TracesTraceTable, TracingGanttChartTraceQueryGreptimeDBTraceQuery

Live examples: catalog.md. Do not use TimeSeriesQuery for logs/traces.

Registered plugins in this app: TimeSeriesChart, StatChart, GaugeChart, Table, LogsTable, TraceTable, TracingGanttChart.

StatChart + sparkline: Only enable sparkline when the query returns a time series (multiple points over time). For scalar / single-value queries (e.g. SELECT count(*) FROM ..., SELECT count(*) FROM ... WHERE ... with no time column), use StatChart without sparkline — omit the field entirely. See reference.md — StatChart.

Table + GROUP BY: Table renders one row per time series, not raw SQL rows. GROUP BY without a TIMESTAMP column in the result collapses to a single row (timestamp + count). Add a synthetic time expression (e.g. to_timestamp_millis(${__to}) AS ts) and put dimensions in non-value columns; hide the synthetic timestamp column in columnSettings. See reference.md — SQL Table.

5. Generate JSON
Single panel (paste into Perses editor)

Output only a Panel object — no dashboard wrapper, no layout, no panel ID map:

json
{
  "kind": "Panel",
  "spec": {
    "display": { "name": "..." },
    "plugin": { "kind": "TimeSeriesChart", "spec": {} },
    "queries": [ ... ]
  }
}

Rules:

  • Top-level kind must be "Panel"
  • Include spec.display.name, spec.plugin, spec.queries
  • Datasource: only sql-default (GreptimeDBDatasource) or promql-default (PrometheusDatasource)
  • User pastes this in Perses edit mode: Add panel → From JSON (or equivalent import)

Optionally append a one-line note with suggested grid size (e.g. width: 24, height: 10).

See reference.md — Single panel.

Full dashboard

Rules:

  • kind: "Dashboard", metadata.project: "default", metadata.version: 0
  • Panel IDs: 32-char lowercase hex (e.g. a8f3c2e1b9044d6a9f7e2c1d0b5a4e32)
  • Layout: 24-column Grid; stack panels vertically (y += previous height)
  • Datasources: reference sql-default or promql-default only — never embed URLs
  • Default duration: "1h", refreshInterval: "30s"
  • spec.datasources: {} (runtime injects globals)

Use helpers from reference.md to build panels and layouts.

6. Validate queries

Before delivering, dry-run every panel query (MCP execute_sql / query_range, or HTTP equivalents on resolved GREPTIME_HOST):

Fix errors before output. Replace ${__from}/${__to} with literal millis when dry-running SQL.

7. Deliver

Single panel: Output pretty-printed Panel JSON only + brief explanation. Do not wrap in Dashboard.

Full dashboard: Output pretty-printed Dashboard JSON + brief explanation (why PromQL vs SQL, which tables/metrics used).

If user asks to save dashboard: Run:

bash
skills/greptimedb-perses-dashboard/scripts/save-dashboard.sh \
  --name <dashboard-name> \
  --file /path/to/dashboard.json \
  [--host "${GREPTIME_HOST:-http://127.0.0.1:4000}"]

Or equivalent curl (see reference.md). Only save when explicitly requested.

Generation modes

Mode A — From table name
Input: public.cpu_metrics_30
→ describe_table → pick TIMESTAMP column from schema (e.g. `ts` on this table)
→ numeric columns = values; string/low-cardinality = tags
→ TimeSeriesChart with GreptimeDBTimeSeriesQuery
Mode B — Natural language (metrics)
Input: "node exporter style CPU/memory monitoring"
→ PromQL path
→ query_range for node_* metrics
→ Gauge + Stat + TimeSeries panels (see [catalog.md §2](catalog.md#2-metrics--promql-prometheustimeseriesquery))
→ Use promql-default; simplify label filters if env-specific labels missing
Mode C — Advanced SQL time series
Input: "temperature trend by location from temp_alerts"
→ SQL path with RANGE/ALIGN
→ describe_table → use schema TIMESTAMP column in WHERE (e.g. `time_window` on temp_alerts)
→ See [catalog.md §1d](catalog.md#1d-range--align-sql-test-dashboard) (RANGE/ALIGN SQL)
Mode D — Unified observability
Input: "dashboard with CPU metrics, logs, and traces"
→ PromQL for metrics panels
→ GreptimeDBLogQuery for logs
→ GreptimeDBTraceQuery for traces
→ Trace **metrics-style** charts (span rate, etc.): GreptimeDBTimeSeriesQuery with to_timestamp_millis(timestamp) AS ts — never raw nanosecond timestamp in TimeSeriesChart
→ Combine in one Grid layout
Mode F — Traces dashboard
Input: "trace dashboard" / public.web_trace_demo
→ describe_table → timestamp is TimestampNanosecond
→ TraceTable / TracingGanttChart: GreptimeDBTraceQuery (raw timestamp OK)
→ StatChart / Table / TimeSeriesChart on same table: GreptimeDBTimeSeriesQuery; chart time column must be millisecond (to_timestamp_millis)
→ Follow Traces Demo for TraceTable shape; avoid ${__from}/${__to} on overview unless data is within dashboard duration
Mode E — Single panel (JSON paste)
Input: "line chart panel for cpu_metrics_30" / "single PromQL CPU gauge panel"
→ Same discovery as Mode A/B/C but output Panel object only
→ kind: "Panel" at root; no metadata, layouts, or panel ID map
→ User pastes into Perses editor when adding a panel

Example output shape — see catalog.md §6.

SQL conventions

  • Time column: always from schema detection (reference.md); use that column name in SQL
  • Timestamp unit: check data_type — for TimestampNanosecond, use to_timestamp_millis(<time_col>) AS ts in GreptimeDBTimeSeriesQuery results; keep raw column only in GreptimeDBTraceQuery (reference.md — Timestamp precision)
  • Time filter: WHERE <time_col> >= to_timestamp_millis(${__from}) AND <time_col> <= to_timestamp_millis(${__to}) (${__from}/${__to} are milliseconds)
  • Aggregation: max(val) RANGE '1m' FILL LINEAR, ALIGN '30s' BY (tag_col)
  • Always LIMIT 2000 (or 100 for tables)
  • Quote identifiers: public."table_name", "column_name"

PromQL conventions

  • Use rate(), avg_over_time(), sum by (label) (...) per standard patterns
  • Reference host-metrics-promql.md in repo for node_exporter examples
  • Datasource name: always promql-default — never ${ds} or other Grafana datasource variables

Additional resources

© GreptimeTeam, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts) in skills/greptimedb-perses-dashboard of GreptimeTeam/dashboard.

  • SKILL.md
  • catalog.md
  • reference.md
  • scripts/save-dashboard.sh

Open the folder on GitHubat commit 1f6e93e

Compare with similar skills

Greptimedb Perses Dashboard next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Greptimedb Perses Dashboard compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Greptimedb Perses Dashboard this skillGreptimeTeam/dashboard111—~3.9kAutomated safety check: PassApache-2.0
Gorm ExpertLeoYeAI/openclaw-master-skills2.2k—~3.4kAutomated safety check: PassMIT
AWS Cost OperationsMicrock/ordinary-claude-skills4041 repos~2.5kAutomated safety check: PassCustom licence
Semantic Analystsidequery/sidemantic129—~982Automated safety check: PassAGPL-3.0
Pytorch Clickhousepytorch/test-infra113—~2.8kAutomated safety check: PassCustom licence
Aurora Dsqlaws/agent-toolkit-for-aws2.8k—~9.6kAutomated safety check: PassApache-2.0

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Questions about Greptimedb Perses Dashboard

What does Greptimedb Perses Dashboard do?

Generate Perses dashboards or single panels for GreptimeDB. An agent skill from GreptimeTeam/dashboard. Greptimedb Perses Dashboard is an agent skill from GreptimeTeam/dashboard. Generate Perses dashboards or single panels for GreptimeDB.

When should I use Greptimedb Perses Dashboard?

Greptimedb Perses Dashboard fits situations like: the user asks to create; scaffold a Perses dashboard; panel from table names; SQL/PromQL queries.

How do I install Greptimedb Perses Dashboard in Claude Code?

Run `npx skills add GreptimeTeam/dashboard --skill greptimedb-perses-dashboard -a claude-code`. Or copy the skill folder (skills/greptimedb-perses-dashboard in GreptimeTeam/dashboard) into .claude/skills/greptimedb-perses-dashboard in your project. Claude Code loads it when a task matches its description.

How do I install Greptimedb Perses Dashboard in Codex?

Run `npx skills add GreptimeTeam/dashboard --skill greptimedb-perses-dashboard -a codex`. Or copy the skill folder (skills/greptimedb-perses-dashboard in GreptimeTeam/dashboard) into .agents/skills/greptimedb-perses-dashboard in your project. Codex loads it when a task matches its description.

Can I use Greptimedb Perses Dashboard in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add GreptimeTeam/dashboard --skill greptimedb-perses-dashboard -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/greptimedb-perses-dashboard, .gemini/skills/greptimedb-perses-dashboard, .github/skills/greptimedb-perses-dashboard and .opencode/skills/greptimedb-perses-dashboard in your project.

What does Greptimedb Perses Dashboard need to run?

Going by SKILL.md and its folder, Greptimedb Perses Dashboard needs a shell for the scripts in its folder and the command-line tools its instructions call (curl and node). Our summary lists: A Bash shell. Compatibility (from SKILL.md): Any Agent Skills or MCP-capable host (Cursor, Claude Desktop/Code, GitHub Copilot, Codex, Gemini CLI, custom agents, etc.); GreptimeDB Dashboard with Perses; data via GreptimeDB MCP server or HTTP API.

Does Greptimedb Perses Dashboard access the network?

SKILL.md names 2 domains. As links in the text: modelcontextprotocol.io and perses.dev. This is read from the text; nothing was executed.

Is Greptimedb Perses Dashboard safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Greptimedb Perses Dashboard use?

Greptimedb Perses Dashboard is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Greptimedb Perses Dashboard use?

About 3.9k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Greptimedb Perses Dashboard?

Skills that share tags, products or a category with Greptimedb Perses Dashboard: Gorm Expert (LeoYeAI/openclaw-master-skills, 2.2k stars), AWS Cost Operations (Microck/ordinary-claude-skills, 404 stars), Semantic Analyst (sidequery/sidemantic, 129 stars) and Pytorch Clickhouse (pytorch/test-infra, 113 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Greptimedb Perses Dashboard?

GreptimeTeam (a GitHub organization) maintains it in GreptimeTeam/dashboard, which has 111 GitHub stars. The repository was last updated on October 10, 2026.

Source: GreptimeTeam/dashboard on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.