网有NETHAVE
AGENT SKILL

token-estimator-mvp

Estimate AI planning ranges from a work description or explicitly authorized safe project context. Provides coarse class ranges or conditional planning bases without requiring token guesses.

License 许可
MIT
最近更新
2026-11-11
Stars
★ 287
Forks
97

01 前言 Front Matter

name
token-estimator-mvp
license
MIT
description
Estimate AI planning ranges from a work description or explicitly authorized safe project context. Provides coarse class ranges or conditional planning bases without requiring token guesses.

02 资源文件 46

03 SKILL.md 正文

Token estimator MVP

Use this skill for first-pass AI planning guidance. It is not a scientific execution service.

Use only the bundled CLI or API with calibration and profiles. Never invent formulas or ask users for token budgets.

Procedure

  1. Identify the deliverable from the request. Context is optional.

  2. Map to the input guide and contract, version 1.2.0.

  3. Leave unknown facts unknown. Provide conditional bases when supported.

  4. For "run an existing workflow," use existing-workflow-operation.

  5. Count shared setup/checks once. Separate independent review as its own task.

  6. Run the estimator with sanitized JSON:

    node scripts/estimate.js --input examples/coarse-prediction.json

  7. Report status, mapping, assumptions, uncertainty and exclusions.

Package notes

Copy this entire directory to skills/token-estimator-mvp/ in the target repository. Keep files relative and project-local. No installs, credentials, network access, or external authoring workspace are required.

See examples for supported scenarios.

Run tests:

node --test tests/model.test.js tests/phases.test.js tests/operations.test.js tests/behavior.test.js tests/packaging.test.js tests/skill-guidance.test.js

This package ships provisional community reference ranges. They are planning heuristics requiring broader community validation and are not statistical bounds or evidence of customer outcomes.

04 同仓库更多 Skills

microsoft
microsoft/discovery

build-research-paper

Cross-domain / Scientific writing and publication — Build beautifully-formatted, arxiv-ready research paper PDFs from a mix of hand-authored LaTeX and/or markdown + PNG figures, using `tectonic` (default) or `pandoc` (escape hatch). Captures the reusable pattern that research projects keep re-discovering: `report/main.tex` + `references.bib` + `generate_figures.py` + iterative feedback/response scaffolding, all buildable with a single command. WHEN: write a research paper, arxiv submission, prepub, generate PDF from markdown, LaTeX paper, build main.tex, journal manuscript, referee revision, response to referee, resubmission package, publication-quality figures, matplotlib publication style, tectonic build, pandoc build, generate arxiv-ready PDF, bibliography from BibTeX.

内容创作者文档处理写作与文案
★ 287
microsoft
microsoft/discovery

add-example-agents

Add agents from the public microsoft/discovery GitHub repository to this workspace, either (a) locally for the Copilot app by emitting a `.agent.md` companion per agent (so each is invocable via `runSubagent`), (b) into a Microsoft Discovery project via `UpsertAgent` sourced fresh from upstream (binding pre-existing tool ARM resources when present, or building + pushing + registering them in Azure first when missing), or (c) promoting an agent already added to the local Copilot app (sourced from its `.github/agents/<name>.agent.md` companion; tool-bearing agents also carry a `discovery_catalog/<name>/` folder plus a locally-built tool container, while toolless agents have only the companion) up to a specific Microsoft Discovery project + Azure without re-fetching or refreshing from upstream. The user picks exactly one of the three targets per run. USE FOR: 'add the discovery agents', 'download discovery agents', 'install all Microsoft discovery agents', 'add agents from microsoft/discovery', 'create copilot agents from microsoft/discovery', 'deploy discovery agents to Foundry', 'deploy discovery agents to Azure', 'promote a local agent to Microsoft Discovery', 'push my local agent and container to a Discovery project', 'copy a local app agent to Azure'. Always refreshes every selected subfolder under `agents/<name>/` of the upstream repo into `discovery_catalog/<name>/` so the local catalog stays current (new agents appear, removed agents are surfaced, updated content is applied). The presence check for what is 'already locally added' uses `.github/agents/<name>.agent.md` (the Copilot companion), not the `discovery_catalog/` folder. For local deployment, each generated `.agent.md` carries a lazy Docker-bootstrap preamble so the agent builds its tool image on first use only if absent. For Discovery + Azure deployment, pre-flights every declared tool via `GetDiscoveryTool` against the workspace's RG and **skips Docker build / ACR push / AcrPull RBAC entirely when the tool already exists** (common for shared catalog images on registries like `mdqacr`); only builds + registers tools that are actually missing. Always creates the agent in the chosen Discovery project via `UpsertAgent` and polls **`GetAgent` for `provisioningState=Succeeded`** (the MCP `GetAgentOperation` tool returns an opaque error in practice; never rely on it). All MCP calls flow through PowerShell scripts embedded in this SKILL.md and materialized into `.vscode/` during Step 4d — the skill does not depend on sibling helper files or on the VS Code MCP runtime surfacing `mcp_microsoft-dis_*` tools mid-session. Local Discovery runtime registration via `agents action=create` is optional and skipped by default. DO NOT USE FOR: running an already-deployed agent (use runSubagent), or editing a single agent's prompt (edit `agent.yaml` directly).

开发工程师运维与部署图像与多媒体
★ 287
microsoft
microsoft/discovery

migrate-podman-containerfile

Migrate a Podman Containerfile to the canonical Dockerfile required by the Discovery catalog. Use when a PR fails POL-022, a tool contains Containerfile or Dockerfile.in, or a contributor asks to convert Podman build files for Docker. Creates the Dockerfile directly only when the migration is mechanically safe and refuses ambiguous preprocessing or multi-file builds.

★ 287
microsoft
microsoft/discovery

discovery-services-starter-kit-deployer

Deploy Discovery catalog starter-kits end-to-end: validate kit.json agentRefs, build and deploy every referenced agent tool, deploy each referenced agent individually, and summarize deployed agents/tools plus customer-ready sample prompts. Use this skill whenever the user asks to deploy a Discovery starter-kit or deploy all agents listed in starter-kits/*/kit.json.

Skill与智能体开发
★ 287
microsoft
microsoft/discovery

discovery-services-agent-deployer

Deploy Discovery catalog agents end-to-end with one command: discover the agent, build and bind its tool when present, skip tool stages for agents without tools, deploy the agent, and optionally run validation. Use this skill whenever the user asks to deploy a Discovery agent, publish or rebuild an agent tool image, register a Discovery tool from a repo Dockerfile/tool.yaml, resume a failed deployment, or produce a dry-run deployment plan for an agent in this catalog.

人力资源运维与部署Skill与智能体开发
★ 287
microsoft
microsoft/discovery

discovery-design-tasks

暂无简介

设计师视觉设计Skill与智能体开发
★ 287