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idmp-workflow-panel-build

idmp-workflow-panel-build is a skill for Claude Code from taosdata/agent-skills. It costs 39 tokens per session (1,410 once invoked), scanned A, original, MIT.

A workflow for building IDMP dashboard panels, which are dashboard sections that display queried data. It resolves ownership, reserves names, creates and checks panels, verifies SQL output, and places panels on dashboards.

In plain words
What is it for?
Use it to draft and create panels, validate their data queries, add them to dashboards, and safely clean up related objects.
Why use it?
It gives panel creation a repeatable process and checks that the resulting query or SQL works before the panel is used.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the idmp-plugin plugin — 23 skills shipped together

not rated 3repo 2d ago A scan 39 tokens original MIT

Good fit Use it to draft and create panels, validate their data queries, add them to dashboards, and safely clean up related objects.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/taosdata/agent-skills/idmp-workflow-panel-build
View source ↗ taosdata/agent-skills
Install

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.

Any agent
npx skills add taosdata/agent-skills --skill idmp-workflow-panel-build
Clone the repo
git clone --depth 1 https://github.com/taosdata/agent-skills

Made for: Claude Code.

Or install idmp-plugin, the plugin that ships this one along with the rest of its 23 skills.

Wrote 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.

agentmods badge for idmp-workflow-panel-build

README.md
[![agentmods](https://agentmods.dev/badge/skills/taosdata/agent-skills/idmp-workflow-panel-build/github.svg)](https://agentmods.dev/skills/taosdata/agent-skills/idmp-workflow-panel-build)
Your own site
<a href="https://agentmods.dev/skills/taosdata/agent-skills/idmp-workflow-panel-build"><img src="https://agentmods.dev/badge/skills/taosdata/agent-skills/idmp-workflow-panel-build/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.

agentmods 80×15 button for idmp-workflow-panel-build

Your own site · 80×15
<a href="https://agentmods.dev/skills/taosdata/agent-skills/idmp-workflow-panel-build"><img src="https://agentmods.dev/badge/skills/taosdata/agent-skills/idmp-workflow-panel-build.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,410 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00039 $0.01410
Opus 5 $0.00019 $0.00705
Sonnet 5 $0.00008 $0.00282
Haiku 4.5 $0.00004 $0.00141

Measured 9d ago against content hash 0503e02847c2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

idmp-workflow-panel-build 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 9d 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.

plugins/idmp-plugin/skills/idmp-workflow-panel-build/SKILL.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

workflow: panel build

Read ../idmp-shared/SKILL.md first.

Missing context to resolve first

  • Whether the request is natural-language friendly enough for AI-first panel drafting.
  • Candidate panel name.
  • Placement plan.
  • AI create prompt seed.
  • idmp-cli ai create create-post --ack-risk --data '{"elementId":123,"prompt":"demo panel prompt","record":true}'
  • idmp-cli panel panels new-name --params '{"elementId":123,"name":"demo-panel"}'
  • Candidate dashboard name.
  • idmp-cli dashboard dashboards new-name --params '{"elementId":123,"name":"demo-dashboard"}'
  • Hierarchy persistence plan.
  • Whether the goal is leaf self, middle self, child aggregation, or a text/manual panel.

Constrained live behaviors

  • Prefer AI draft-first create for natural-language panel requests: POST /api/v1/ai/panels/create first, then persist the returned draft through panel.panels.create.
  • panel verify create is the time-range-only validator and does not take owner --params.
  • panel verify create-post validates advanced SQL entries.
  • Creating a panel does not place it into a dashboard.
  • panel.params owns the panel time range.
  • dashboard.params owns dashboard refresh settings.
  • If generated SQL is empty, stop before persistence.
  • Every advanced fallback must keep a valid advancedQueryType.
  • panel.panels.query and panel.panels.create use the panel DTO shape.
  • Keep checked boolean and dimensions as an array of strings.
  • Standard child-scope roundtrips can collapse back to self scope.
  • Persist the advanced fallback only after reread shows enableAdvanced=true; save that SQL with enableAdvanced=true. A verified advanced fallback still counts as first-attempt success for child-scope panel work.
  • Empty-body 400 responses usually mean the payload shape is wrong.
  • AI panel drafts can include an id; remove it before persistence. If the AI draft collapses child scope, loses required placement fields, or fails to persist, fall back to the existing structured workflow.

Read the full file on GitHub · 88 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 9d ago First seen · 88 lines · 39 tokens per session scan A 0503e02847c2

Subscribe to this mod's changes

idmp-workflow-panel-build is a skill published in the GitHub repository taosdata/agent-skills (3 stars, last pushed 2d ago), licensed MIT. It adds 39 tokens to every session and 1,410 once invoked, about $0.0002 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 2026-08-30.

Analytics and metricsDatabases
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