What is painpoint-research?

An evidence-gathering workflow for finding problems that matter to a defined audience. A painpoint is a recurring difficulty, frustration, or unmet need that content may address.

Use it to research and score audience problems for a confirmed project, retain source records, submit research batches, and review individual findings.

It creates traceable research records without made-up sources or unsupported claims, and pauses for review before writing begins.

painpoint-research — Skill for Codex by zhuangguangdahyh-dotcom

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 zhuangguangdahyh-dotcom/content-ops-studio --skill painpoint-research

Clone the repo

git clone --depth 1 https://github.com/zhuangguangdahyh-dotcom/content-ops-studio

Made for: Codex.

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/zhuangguangdahyh-dotcom/content-ops-studio/painpoint-research/github.svg)](https://agentmods.dev/skills/zhuangguangdahyh-dotcom/content-ops-studio/painpoint-research)

Your own site

<a href="https://agentmods.dev/skills/zhuangguangdahyh-dotcom/content-ops-studio/painpoint-research"><img src="https://agentmods.dev/badge/skills/zhuangguangdahyh-dotcom/content-ops-studio/painpoint-research/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/zhuangguangdahyh-dotcom/content-ops-studio/painpoint-research"><img src="https://agentmods.dev/badge/skills/zhuangguangdahyh-dotcom/content-ops-studio/painpoint-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 47 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,092 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.

Model	Per session	Once invoked
Fable 5.1	$0.00047	$0.01092
Opus 5	$0.00023	$0.00546
Sonnet 5	$0.00009	$0.00218
Haiku 4.5	$0.00005	$0.00109

Measured 11d ago against content hash 74295e627391, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

painpoint-research 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.

plugins/content-ops-studio/skills/painpoint-research/SKILL.md · 71 lines

How it starts

The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Purpose

Create a recoverable, evidence-backed painpoint batch without padding, fabricated sources, or premature content production.

Use this skill when

The Operator wants painpoint research for a project that is PROJECT_ACTIVE and CONFIG_CONFIRMED, or wants to inspect/review an existing research batch.

Do not use this skill when

Project configuration is not confirmed, material Profile gaps remain, the request is final copy or image production, or no source path is available.

Required preflight

Call content_ops_get_research_context. Verify Profile readiness; Platform/Industry Pack versions; active rules and rejected directions; existing painpoints/content summaries; research capability; and G1 evidence. Keep Operator, Subject and Audience distinct.

Required tool sequence

Call content_ops_plan_painpoint_research. Default to 30 requested items, but never promise that count.
The host searches/opens current public sources with host-native tools, or the Operator supplies bounded manual sources. The MCP server never searches or fetches the internet.
Call content_ops_submit_research_sources with URL or project-relative locator, source metadata, bounded summary, supported claims, limitations, first-party flags, and content hash.
Analyze the evidence semantically in the host. Call content_ops_submit_painpoint_candidates; every candidate must reference evidence, carry A/B/C/D confidence, and include deterministic 0–5 score dimensions.
Call content_ops_finalize_painpoint_research only after explicit write confirmation. Runtime validates, writes pending painpoints idempotently, read-verifies and stops at G2 PAINPOINTS.
Show the retained batch to the Operator. Record per-item APPROVE / REVISE / REJECT / PAUSE decisions before calling existing content_ops_submit_approval for the matching batch and version.
Use content_ops_list_painpoints, content_ops_get_painpoint, and content_ops_verify_painpoint_batch for readback and verification.

Read the full file on GitHub · 71 lines

Files

What ships with it

7 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 First seen · 71 lines · 47 tokens per session scan A 74295e627391

Subscribe to this mod's changes

painpoint-research is a skill published in the GitHub repository zhuangguangdahyh-dotcom/content-ops-studio (0 stars, last pushed 15d ago), licensed MIT. It adds 47 tokens to every session and 1,092 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 2026-08-31.

Marketing and SEO Research ai codex content-operations content-workflow feishu image-generation

gpt-image

Generate or edit images with GPT Image 2 or 2.5 through the packaged CLI and Reference Gallery. Use for image requests including imprecise 'GPT 2.5' model names, posters, typography, reference edits, and inpainting; resolve the model choice before generation.

wuyoscar/GPT-Image2-Skill · 62 tokens

get-prompt-from-image

Analyze user-provided reference images and reverse-engineer high-fidelity AI image-generation prompts. Use when the user asks to recreate, imitate, reverse-engineer, or extract prompts from photographs, illustrations, 3D renders, products, characters, landscapes, typography, logos, posters, or other visual references.…

wuyoscar/GPT-Image2-Skill · 83 tokens

painpoint-research