A general-purpose connection to the ClickUp API, the interface that lets software read and change ClickUp data. It supports custom requests when a more specific task operation is not available.

Use it to make custom GET, POST, PUT, or DELETE requests for ClickUp tasks, documents, chat, attachments, time tracking, task moves, or audit logs.

It removes the need to build separate request code for each ClickUp endpoint. It also lets you work with both ClickUp API version 2 and version 3 where supported.

fde — Skill for Claude Code and Codex by suboss87/FDEOps

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 suboss87/FDEOps --skill fde

Clone the repo

git clone --depth 1 https://github.com/suboss87/FDEOps

Made for: Claude Code, Codex.

Or install fdeops, the plugin that ships this one along with the rest of its 35 skills, 5 commands, 3 hooks.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/suboss87/fdeops/fde/github.svg)](https://agentmods.dev/skills/suboss87/fdeops/fde)

Your own site

<a href="https://agentmods.dev/skills/suboss87/fdeops/fde"><img src="https://agentmods.dev/badge/skills/suboss87/fdeops/fde/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/suboss87/fdeops/fde"><img src="https://agentmods.dev/badge/skills/suboss87/fdeops/fde.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 125 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,554 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. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 3 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium MCP Rug Pull · line 3
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium MCP Rug Pull · line 53
npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.

Fix: Pin the version: npx @scope/[email protected]
medium Rogue Agent · line 35
Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.

Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.

How audits are shown

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.

Model	Per session	Once invoked
Fable 5.1	$0.00125	$0.02554
Opus 5.5	$0.00050	$0.01022
Sonnet 5.5	$0.00025	$0.00511
Haiku 4.5	$0.00013	$0.00255

Measured 11d ago against content hash 1b1978b86b74, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

fde 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 11d 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.

skills/fde/SKILL.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

@fde

Purpose

Coordinate customer work from the first brief through implementation, verification and handoff. Choose the relevant task; never make the user pick a phase. All task skills also work individually. Reuse the customer's tools, decisions and operating process.

Task entry

Read references/task-context.md for authority, data boundaries, CLI availability and evidence rules. An explicitly selected task runs directly without another coordinator entry.

Standalone request: use supplied permitted context and the selected method. Do not initialize .fde/, preferences or records just to draft, analyze or change code. Ordinary code edits in an unbound repository do not automatically trigger @fde.
Ongoing engagement: use the supplied customer binding. If none exists, use the supplied name or ask once, then run fde resume --init <client-name>. Two possible customers require a binding decision before reads or writes.
Ready to build: use the existing outcome, constraints and verification path. Discover or plan only for material gaps. Audit inherited claims on a takeover.

Human surface vs agent plumbing

The human asks in ordinary language or invokes a task skill. You run the required CLI commands. Never tell the FDE to type commands; never ask them to run the CLI. Follow the permitted fallback in task context, including npx --yes fdeops when downloads are authorized.

Entry (every session)

Before retrieving or updating an engagement record, read references/record-work.md for privacy-safe session entry, record commands, the memory contract and session digest. Load it once for the current task; standalone work does not require it. Confirm consequential record changes under task-context rules. A saved claim is not customer acceptance.

Engineering and delivery

Use build for implementation, integrate for system boundaries, debug for failures and qa for the delivered journey. Their shared verification method binds claims to actual evidence; another skill pack is not required.

Read the full file on GitHub · 133 lines

Files

What ships with it

46 files 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.

11d ago Changed · -53 lines 1b1978b86b74
28d ago Changed · +6 lines 149f17b28e75
29d ago Changed · -55 lines 9f6d9ebc35c8
1mo ago Changed · +11 lines 7bdd6e618cab
1mo ago Changed a698acf4ee3c
1mo ago Changed · +10 lines 62a65a86aad1
1mo ago Changed · +5 lines 149f78ca04d0
1mo ago Changed 63604bda01c6
1mo ago Changed · +2 lines 812eb15dbb1c
1mo ago First seen · 207 lines · 125 tokens per session scan A 88847ba3ec17

Subscribe to this mod's changes

fde is a skill published in the GitHub repository suboss87/FDEOps (967 stars, last pushed 8d ago), licensed MIT. It adds 125 tokens to every session and 2,554 once invoked, about $0.0005 per session on Opus 5.5. 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.

Project management ai-agents claude-skills codex-skill cursor fde forward-deployed-engineering

meta-ad-manager

Front door and loop owner of a Meta (Facebook/Instagram) ad harness. Reads the brand's ads/ docs, works out which campaign the user means and which stage it is at, hands off to the stage skill that runs it (intake, strategy, creative, launch, checks, fixes, answers), and writes every stage change back to the docs. Use…

gooseworks-ai/goose-skills · 108 tokens

help-center-article-generator

Take support ticket clusters, FAQ patterns, product documentation, or feature specs and generate structured help center articles with step-by-step instructions, screenshot placeholders, troubleshooting sections, and related article links. Batch mode generates multiple articles from a ticket export. Pure reasoning…

gooseworks-ai/goose-skills · 57 tokens

contact-cache

Track all identified/contacted people across strategies. CSV-backed contact database with dedup by LinkedIn URL or email. Prevents duplicate outreach when running strategies on a recurring cadence.

gooseworks-ai/goose-skills · 38 tokens

mass-ulw

Drives dependency-ordered child work through the native workflow tool, each phase's stages defined up front in one run, with retry/amend/send recovery. Use when the user asks for mass-ulw, a DAG of tasks, or fan-out work where some tasks must wait on others.

code-yeongyu/oh-my-openagent · 62 tokens

github-triage

Read-only GitHub triage for issues AND PRs. 1 item = 1 background task (category: quick). Analyzes all open items and writes evidence-backed reports to /tmp/{datetime}/. Every claim requires a GitHub permalink as proof. NEVER takes any action on GitHub - no comments, no merges, no closes, no labels. Reports only.…

code-yeongyu/oh-my-openagent · 104 tokens

prioritization

Framework-driven feature and initiative prioritization using RICE, ICE, or weighted scoring. Grounds prioritization in strategic pillars and demands evidence-based scoring. Trigger phrases: "prioritize features", "prioritization", "rank these initiatives", "RICE score", "ICE score", "what should we build next"…

aniganti/pm-superpowers · 73 tokens