Build a deduplicated editorial backlog from current, traceable demand and authoritative product evidence.

MIT-0Auto-check passedDevelopment

Install Blog Topic Research

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill blog-topic-research -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace blog-topic-research --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/productivity/publishing-skills/skills/blog-topic-research .claude/skills/blog-topic-research && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
blog-topic-research
GitHub stars
2.8k
Token cost
~2k tokens
SKILL.md length
799 words
Files
1
Skills in repo
3,342
Repo updated
First seen
Licence
MIT-0

At a glance

Build a deduplicated editorial backlog from current, traceable demand and authoritative product evidence.

  • Works in 11 steps: Confirm scope, audience, locale, time… → Read the existing coverage inventory.… → Search across at least three suitable… → …
  • Deciding which long-tail topics are worth writing before drafting begins
  • SKILL.md covers Overview, Prerequisites, Tool Discipline and Instructions, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Blog Topic Research is an agent skill from jeremylongshore/tons-of-skills-marketplace. Build a deduplicated editorial backlog from current, traceable demand and authoritative product evidence. Use when deciding which long-tail topics are worth writing before drafting begins. Trigger with "research blog topics" or "find evidence-backed content ideas".

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Designed for Claude Code; search evidence changes over time, and backlog writes require editorial approval plus revalidation of source currency

It sits in Development. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT-0.

When your agent uses it

  • Deciding which long-tail topics are worth writing before drafting begins
  • With research blog topics
  • Find evidence-backed content ideas

Example prompts

  • “research blog topics”
  • “find evidence-backed content ideas”
  • “/blog-topic-research”

Requirements

  • Compatibility (from SKILL.md): Designed for Claude Code; search evidence changes over time, and backlog writes require editorial approval plus revalidation of source currency
  • Pre-approved tools (allowed-tools): Read, WebSearch, WebFetch, Write, Edit

Workflow steps

11 steps, taken from the first numbered list in SKILL.md.

  1. Confirm scope, audience, locale, time horizon, count, excluded subjects, and the publication's definition of a useful conversion or reader…
  2. Read the existing coverage inventory. Normalize case, punctuation, product names, versions, error codes, and canonical URLs while…
  3. Search across at least three suitable signal classes: official docs or changelogs, public issue trackers, vendor forums, Stack Overflow…
  4. Fetch each candidate source. Capture its title, URL, publication or update date when available, exact short evidence excerpt, source type…
  5. Pair demand evidence with at least one current authoritative source whenever the topic makes product, API, version, legal, medical…
  6. Classify search intent and format: how-to-fix, how-to-connect, how-to-automate, x-vs-y, what-is, use-case, listicle, migration, or…
  7. Score evidence explicitly. Use 1 for a single relevant public mention, 2 for repeated or engaged discussion, and 3 for strong repeated…
  8. Run duplicate checks against published and planned coverage. Reject a matching canonical intent; flag near matches that differ only by…
  9. Extract only supported problem summaries, fix kernels, version constraints, and question variants. Mark unresolved or conflicting answers…
  10. Rank accepted topics by evidence, business relevance, authority availability, coverage gap, and freshness. Explain the factors and report…
  11. Present the candidate set for approval. Append only accepted records to the requested path, preserving stable IDs and source timestamps.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • WebSearch
    • WebFetch
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • developers.google.com
    • support.google.com
    • docs.github.com
    • api.stackexchange.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code; search evidence changes over time, and backlog writes require editorial approval plus revalidation of source currency

    From compatibility in the SKILL.md frontmatter.

Context cost

Blog Topic Research loads about 2k tokens when it runs. Until then it costs about 71 tokens; SKILL.md has 799 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~71
When it runs · the whole SKILL.md, loaded when a task matches
~2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT-0 licence (© jeremylongshore). 799 words, ~2,008 tokens.

Download SKILL.mdSave it as .claude/skills/blog-topic-research/SKILL.md (or your agent's skills folder).
name
blog-topic-research
description
Build a deduplicated editorial backlog from current, traceable demand and authoritative product evidence. Use when deciding which long-tail topics are worth writing before drafting begins. Trigger with "research blog topics" or "find evidence-backed content ideas".
allowed-tools
Read, WebSearch, WebFetch, Write, Edit
compatibility
Designed for Claude Code; search evidence changes over time, and backlog writes require editorial approval plus revalidation of source currency
argument-hint
[count] [cluster-or-product] [--append-to path]
version
1.2.0
author
AutomateLab <hello@automatelab.tech>
license
MIT-0
tags
seo, topic-research, search-intent, content-strategy, evidence
model
inherit
effort
high

Evidence-Backed Blog Topic Research

Overview

Find specific editorial opportunities supported by real user questions and current primary sources. Each accepted topic includes an evidence trail, search intent, version context, known-answer status, and duplicate-risk decision.

This workflow does not invent search volume or treat autocomplete as proof of commercial value. It separates observed demand from editorial judgment.

Prerequisites

  • Target audience, product or subject boundary, business goal, locale, and preferred language
  • Existing titles, canonical URLs, slugs, and planned backlog for cannibalization checks
  • Approved topic clusters and formats, if the publication uses a taxonomy
  • Current access to public search results, official documentation, changelogs, issue trackers, and relevant community sources
  • A requested count between 1 and 100; default to 25 when omitted

Tool Discipline

Use Read for the supplied inventory and taxonomy. Use WebSearch to discover candidate questions and WebFetch to verify the actual source page, date, title, and context. Use Write or Edit only after the user approves backlog changes; do not store private community data, credentials, or unnecessary personal information.

Instructions

  1. Confirm scope, audience, locale, time horizon, count, excluded subjects, and the publication's definition of a useful conversion or reader outcome.
  2. Read the existing coverage inventory. Normalize case, punctuation, product names, versions, error codes, and canonical URLs while preserving the original titles.
  3. Search across at least three suitable signal classes: official docs or changelogs, public issue trackers, vendor forums, Stack Overflow, Reddit, or visible search suggestions. Respect access controls and site terms.
  4. Fetch each candidate source. Capture its title, URL, publication or update date when available, exact short evidence excerpt, source type, and whether it is primary or community evidence.
  5. Pair demand evidence with at least one current authoritative source whenever the topic makes product, API, version, legal, medical, financial, performance, or pricing claims.
  6. Classify search intent and format: how-to-fix, how-to-connect, how-to-automate, x-vs-y, what-is, use-case, listicle, migration, or release-recap.
  7. Score evidence explicitly. Use 1 for a single relevant public mention, 2 for repeated or engaged discussion, and 3 for strong repeated demand across independent sources. Label this an editorial signal score, never search volume.
  8. Run duplicate checks against published and planned coverage. Reject a matching canonical intent; flag near matches that differ only by phrasing; preserve distinct version, error, integration-pair, or audience qualifiers when justified.
  9. Extract only supported problem summaries, fix kernels, version constraints, and question variants. Mark unresolved or conflicting answers instead of resolving them from model memory.
  10. Rank accepted topics by evidence, business relevance, authority availability, coverage gap, and freshness. Explain the factors and report any shortfall rather than padding the list.
  11. Present the candidate set for approval. Append only accepted records to the requested path, preserving stable IDs and source timestamps.

Evidence Contract

Each accepted record should contain:

json
{
  "topic": "How to diagnose webhook signature failures after key rotation",
  "cluster": "integrations",
  "format": "how-to-fix",
  "intent": "troubleshooting",
  "signal_score": 3,
  "demand_signals": [
    {
      "type": "github_issue",
      "url": "https://example.com/public-issue",
      "evidence": "Short exact title or question",
      "observed_at": "2026-09-11"
    }
  ],
  "primary_sources": ["https://example.com/current-official-doc"],
  "version_context": "verify at drafting time",
  "duplicate_decision": "accept",
  "duplicate_matches": []
}

Keep excerpts short and attributable. A URL that no longer contains the claimed evidence does not satisfy the contract.

Show full SKILL.md (320 more words)Show less

Approval Boundaries

Do not bypass robots controls, authentication, rate limits, paywalls, or community privacy expectations. Do not write to the editorial backlog, contact source authors, or turn sensitive anecdotes into content without explicit approval. Treat health, legal, financial, and security topics as requiring qualified review.

Output

Return:

  • scope and research timestamp
  • ranked accepted candidates with factor-level rationale
  • evidence and primary-source URLs per topic
  • rejected candidates with duplicate, weak-evidence, stale-source, or out-of-scope reasons
  • coverage gaps, conflicts, and the number of requested topics not found
  • append preview and final write receipt when approved

Error Handling

ConditionResponse
Search result cannot be fetchedDo not use its snippet as verified evidence; find an accessible primary page or reject it.
Source dates or versions conflictPreserve both, lower confidence, and require revalidation during drafting.
Existing coverage inventory is absentRun title-level checks on supplied context, mark cannibalization incomplete, and do not claim uniqueness.
Evidence contains personal or sensitive dataMinimize or omit it and retain only the public question needed for editorial evaluation.
Fewer qualified topics than requestedReturn the valid subset and a source-by-source shortfall report.
Append target changed during reviewRe-read, rerun duplicate checks, and preview the merged result before writing.

Examples

Research a focused backlog:

text
request: 10 topics for the integrations cluster
accepted: 7
rejected: 2 duplicate intents, 1 stale unsupported version claim
top candidate: webhook signature failures after key rotation
evidence: public issue + current vendor verification guide
append: awaiting approval

Reject a plausible but unsupported idea:

text
candidate: "Best automation platform for every startup"
result: reject
reason: vague intent, no measurable comparison contract, and no qualifying demand evidence

Verification

  • Re-fetch every selected URL and confirm it supports the stored title or excerpt.
  • Confirm every factual or version-sensitive topic has a primary source.
  • Confirm accepted titles pass the same duplicate checks against published and planned coverage.
  • Confirm no score is described as monthly search volume unless it comes from a named, current data provider.
  • Confirm appended record count and IDs match the approved preview.

Resources

Next Steps

Pass approved records to blog-editorial-calendar. Re-fetch the decisive sources when drafting because questions, documentation, and product behavior can change.

© jeremylongshore, MIT-0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/productivity/publishing-skills/skills/blog-topic-research of jeremylongshore/tons-of-skills-marketplace.

Open the folder on GitHubat commit cfae287

Compare with similar skills

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Categories

Questions about Blog Topic Research

What does Blog Topic Research do?

Build a deduplicated editorial backlog from current, traceable demand and authoritative product evidence. Blog Topic Research is an agent skill from jeremylongshore/tons-of-skills-marketplace. Build a deduplicated editorial backlog from current, traceable demand and authoritative product evidence.

When should I use Blog Topic Research?

Blog Topic Research fits situations like: deciding which long-tail topics are worth writing before drafting begins; with research blog topics; find evidence-backed content ideas.

How do I install Blog Topic Research in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill blog-topic-research -a claude-code`. Or copy the skill folder (plugins/productivity/publishing-skills/skills/blog-topic-research in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/blog-topic-research in your project. Claude Code loads it when a task matches its description.

How do I install Blog Topic Research in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill blog-topic-research -a codex`. Or copy the skill folder (plugins/productivity/publishing-skills/skills/blog-topic-research in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/blog-topic-research in your project. Codex loads it when a task matches its description.

Can I use Blog Topic Research in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill blog-topic-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/blog-topic-research, .gemini/skills/blog-topic-research, .github/skills/blog-topic-research and .opencode/skills/blog-topic-research in your project.

What does Blog Topic Research need to run?

SKILL.md names no scripts, command-line tools or credentials: Blog Topic Research is instructions for the agent only. Its frontmatter pre-approves these tools: Read, WebSearch, WebFetch, Write, Edit. Compatibility (from SKILL.md): Designed for Claude Code; search evidence changes over time, and backlog writes require editorial approval plus revalidation of source currency.

Does Blog Topic Research access the network?

SKILL.md names 4 domains. As links in the text: developers.google.com, support.google.com, docs.github.com and api.stackexchange.com. This is read from the text; nothing was executed.

Is Blog Topic Research safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Blog Topic Research use?

Blog Topic Research is published under the MIT-0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Blog Topic Research use?

About 2k tokens (SKILL.md is roughly 8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Blog Topic Research?

Skills that share tags, products or a category with Blog Topic Research: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 297k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Blog Topic Research?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.