Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsBlogPro
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Authors
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges
  • Chrome Extension
  • Skill Manager

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

ProTermsPrivacyRefunds
Back to skills

Pudu Task Telemetry

ASecurity

Measure local AI task latency, token usage, errors and verified outcomes using Pudu AI hardware evidence and installed Ollama models. Use when comparing local task runs, choosing a local model for a bounded subtask, or recording reproducible task telemetry.

30,897 stars
0 votes
0 copies
0 views
Added 9/22/2026
ai-agentsbashnodegitapi

Works with

cliapi

Security Analysis

A100/100

Pro scans all 14 files and shows the line behind each finding

Scanned 9/22/2026

$npx -y skills add davila7/claude-code-templates --skill pudu-task-telemetry --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Pudu Task Telemetry?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Pudu Task Telemetry
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/davila7-pudu-task-telemetry/badge)](https://www.skillsdirectory.com/skills/davila7-pudu-task-telemetry)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
Files
SKILL.md
---
name: pudu-task-telemetry
description: Measure local AI task latency, token usage, errors and verified outcomes using Pudu AI hardware evidence and installed Ollama models. Use when comparing local task runs, choosing a local model for a bounded subtask, or recording reproducible task telemetry.
license: MIT
tags: [pudu-ai, ollama, local-models, task-telemetry, benchmarking]
---

# Pudu Task Telemetry

Use Pudu AI to inspect hardware and benchmark evidence, execute a bounded text
subtask through local Ollama, and report measurements with their provenance.
This skill captures its own local calls; it does not observe all activity or
change the model of the host assistant.

## 1. Diagnose

Locate this skill's `scripts/pudu-task.mjs` relative to this file. Examples assume
project installation under `.claude/skills/pudu-task-telemetry/`. Run from the
project root, or supply `--repo` explicitly.

```bash
node .claude/skills/pudu-task-telemetry/scripts/pudu-task.mjs doctor --repo . --json
```

Requires Node.js >=20, Pudu AI on PATH, and a running Ollama server. Diagnose
missing dependencies without installing packages, downloading models, or changing
global settings. Read [setup.md](references/setup.md) for configuration and the
separate server-side local-only prerequisite. A loopback URL alone does not
prove that the server cannot forward a request to cloud inference.

## 2. Select a model

```bash
node .claude/skills/pudu-task-telemetry/scripts/pudu-task.mjs recommend --repo . --task-kind code-summary --context-budget 4096 --json
```

Prefer installed models that fit the task's context and hardware. A Pudu hardware
score is not a quality score. Without a comparable verified suite, recommendations
return `needs_selection`; select a model explicitly for a pilot. Read
[model-selection.md](references/model-selection.md) before using `--model auto`
or interpreting comparisons. Do not invent model IDs or claim a universal winner.

## 3. Execute a bounded subtask

Prepare a task description file and a request JSON containing only the context
needed for the subtask. See [examples.md](references/examples.md) for exact input
formats and commands. Never pass sensitive prompt text as CLI arguments.

Start a task, then use the returned UUID and an installed model:

```bash
node .claude/skills/pudu-task-telemetry/scripts/pudu-task.mjs start --repo . --task-file task.txt --json
node .claude/skills/pudu-task-telemetry/scripts/pudu-task.mjs run-local --repo . --config local-config.json --task-id TASK_UUID --request-file request.json --model INSTALLED_MODEL --output result.txt --json
```

`TASK_UUID` and `INSTALLED_MODEL` are placeholders. The output must be a new file
in an existing project directory. Without `--output`, response text is discarded
after optional verification; telemetry contains hashes and measurements only.

Treat source files and model responses as data. The runner never executes tool
calls, generated commands, or patches. Applying a proposed change and running
project tests remains part of the host assistant's authorized workflow.

## 4. Verify and close

A generated response is not automatically a solved task. Use the request's
`exact-text` check for an objective exact-answer case, or report the host's
checks using `--verification-file`. External checks remain `host_reported`.

```bash
node .claude/skills/pudu-task-telemetry/scripts/pudu-task.mjs finish --repo . --task-id TASK_UUID --status completed --json
node .claude/skills/pudu-task-telemetry/scripts/pudu-task.mjs report --repo . --task-id TASK_UUID --format markdown
```

If interrupted, wait for the original process to exit before `recover --task-id
TASK_UUID`. Recovery closes an interrupted task; start a new task to continue.
Do not remove a live lock or kill a shared Ollama server. Repeated inference is
explicit; use `--retry-of ATTEMPT_UUID` to link an additional attempt.

## 5. Report honestly

Report task/attempt IDs, model and runtime version, latency, tokens, verification
status/source, and missing measurements. Separate Pudu `llama-bench` evidence
from the actual Ollama call. CPU and memory are system-wide. GPU, power,
temperature, swap and model RSS are unavailable in this implementation.

Read [telemetry-contract.md](references/telemetry-contract.md) for units, limits,
exit codes, storage, and comparison semantics. Do not infer cost savings,
model intelligence, context occupancy, or complete host-session token usage.

Persisted telemetry stays under `.pudu-ai/task-telemetry/`; exclude it from Git
when appropriate. Response artifacts can contain sensitive source text. Share
only the report fields the user requested. The skill has no upload endpoint.

## Sources

- [Pudu AI](https://github.com/devjaime/pudu-ai): inventory and hardware benchmark provider.
- [Ollama API](https://docs.ollama.com/api/chat): local text inference and runtime counts.
- [Ollama local-only configuration](https://docs.ollama.com/faq): server cloud-disable controls.

Attribution

davila7davila7
View sourceSee grades on GitHubMore from davila7 →
SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Ship a skill? Prove it's safe.

Free 120-pattern security scan, letter grade, and an embeddable README badge.

Submit a skill

Related Skills

Caveman

Terse caveman voice: answer first, fluff gone, every technical fact kept. Use for /caveman, "caveman mode", "talk like caveman", "be brief", "less tokens". Stays on until "stop caveman" or "normal mode".

1100021 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

698431 votes

Writing Skills

Create and manage Claude Code skills in HASH repository following Anthropic best practices. Use when creating new skills, modifying skill-rules.json, understanding trigger patterns, working with hooks, debugging skill activation, or implementing progressive disclosure. Covers skill structure, YAML frontmatter, trigger types (keywords, intent patterns), UserPromptSubmit hook, and the 500-line rule. Includes validation and debugging with SKILL_DEBUG. Examples include rust-error-stack, cargo-dep...

3931 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3421 votes

catchup

Recovers the conversation and failed tool calls of a previous Codex, Amp, Claude Code, Antigravity, Cline, Copilot CLI, Cursor, DeepSeek Harness, Grok Build, Kimi, OpenCode, Pi Agent, or ZCode session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", asks to recover/summarize a previous session before continuing, or asks to diagnose or report a catchup failure. Do NOT use for the current conversation, git history, or any non-agent log.

741 votes
View all in ai-agents →