New: 98,000+ skills indexed from GitHub repos with 100+ stars · every skill safety-checkedBrowse top skillsTop skills
Esc to closeBrowse all skills
Submit a skillBrowse skills
Submit a skillBrowse skills

Agent skill

Research Ops

by affaan-m in affaan-m/ECC

Evidence-first current-state research workflow for ECC. An agent skill from affaan-m/ECC.

MITAuto-check passedResearch & Science

Install Research Ops

skills CLI
$ npx skills add affaan-m/ECC --skill research-ops -a claude-code

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

GitHub CLI
$ gh skill install affaan-m/ECC research-ops --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/affaan-m/ECC.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research-ops .claude/skills/research-ops && 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
research-ops
GitHub stars
277k
Used in
2 other repos
Token cost
~902 tokens
SKILL.md length
435 words
Files
1
Skills in repo
683
Repo updated
First seen
Licence
MIT

At a glance

Evidence-first current-state research workflow for ECC. An agent skill from affaan-m/ECC.

  • Works in 5 steps: Start from what the user already gave you → Classify the ask → Take the lightest useful evidence path… → …
  • The user wants fresh facts
  • SKILL.md covers Skill Stack, When to Use, Guardrails and Workflow, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Research Ops is an agent skill from affaan-m/ECC. Evidence-first current-state research workflow for ECC. Use when the user wants fresh facts, comparisons, enrichment, or a recommendation built from current public evidence and any supplied local context.

Its SKILL.md is about 900 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science. It works with Exa. The repository describes itself as: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. The licence is MIT.

When your agent uses it

  • The user wants fresh facts
  • A recommendation built from current public evidence and any supplied local context

Example prompts

  • “/research-ops”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Start from what the user already gave you
  2. Classify the ask
  3. Take the lightest useful evidence path first
  4. Report with explicit evidence boundaries
  5. Decide whether the task should stay manual

What it can do on your machine

Read from SKILL.md and the folder at commit 2d515e4. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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.

Context cost

Research Ops loads about 902 tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 435 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~902

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 affaan-m/ECC at commit 2d515e4, republished under its MIT licence (© affaan-m). 435 words, ~902 tokens.

Download SKILL.mdSave it as .claude/skills/research-ops/SKILL.md (or your agent's skills folder).
name
research-ops
description
Evidence-first current-state research workflow for ECC. Use when the user wants fresh facts, comparisons, enrichment, or a recommendation built from current public evidence and any supplied local context.
metadata.origin
ECC

Research Ops

Use this when the user asks to research something current, compare options, enrich people or companies, or turn repeated lookups into a monitored workflow.

This is the operator wrapper around the repo's research stack. It is not a replacement for deep-research, exa-search, or market-research; it tells you when and how to use them together.

Skill Stack

Pull these ECC-native skills into the workflow when relevant:

  • exa-search for fast current-web discovery
  • deep-research for multi-source synthesis with citations
  • market-research when the end result should be a recommendation or ranked decision
  • lead-intelligence when the task is people/company targeting instead of generic research
  • knowledge-ops when the result should be stored in durable context afterward

When to Use

  • user says "research", "look up", "compare", "who should I talk to", or "what's the latest"
  • the answer depends on current public information
  • the user already supplied evidence and wants it factored into a fresh recommendation
  • the task may be recurring enough that it should become a monitor instead of a one-off lookup

Guardrails

  • do not answer current questions from stale memory when fresh search is cheap
  • separate:
    • sourced fact
    • user-provided evidence
    • inference
    • recommendation
  • do not spin up a heavyweight research pass if the answer is already in local code or docs

Workflow

1. Start from what the user already gave you

Normalize any supplied material into:

  • already-evidenced facts
  • needs verification
  • open questions

Do not restart the analysis from zero if the user already built part of the model.

2. Classify the ask

Choose the right lane before searching:

  • quick factual answer
  • comparison or decision memo
  • lead/enrichment pass
  • recurring monitoring candidate
Show full SKILL.md (170 more words)Show less
3. Take the lightest useful evidence path first
  • use exa-search for fast discovery
  • escalate to deep-research when synthesis or multiple sources matter
  • use market-research when the outcome should end in a recommendation
  • hand off to lead-intelligence when the real ask is target ranking or warm-path discovery
4. Report with explicit evidence boundaries

For important claims, say whether they are:

  • sourced facts
  • user-supplied context
  • inference
  • recommendation

Freshness-sensitive answers should include concrete dates.

5. Decide whether the task should stay manual

If the user is likely to ask the same research question repeatedly, say so explicitly and recommend a monitoring or workflow layer instead of repeating the same manual search forever.

Output Format

text
QUESTION TYPE
- factual / comparison / enrichment / monitoring

EVIDENCE
- sourced facts
- user-provided context

INFERENCE
- what follows from the evidence

RECOMMENDATION
- answer or next move
- whether this should become a monitor

Pitfalls

  • do not mix inference into sourced facts without labeling it
  • do not ignore user-provided evidence
  • do not use a heavy research lane for a question local repo context can answer
  • do not give freshness-sensitive answers without dates

Verification

  • important claims are labeled by evidence type
  • freshness-sensitive outputs include dates
  • the final recommendation matches the actual research mode used

© affaan-m, MIT. 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 skills/research-ops of affaan-m/ECC.

Open the folder on GitHubat commit 2d515e4

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in affaan-m/ECC, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Research Ops next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Research Ops compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research Ops this skillaffaan-m/ECC277k2 repos~902Automated safety check: PassMIT
Deep Science WriterCYC2002tommy/Deep-Research-Agent311—~8.7kAutomated safety check: WarnMIT
Exa SearchBioTender-max/awesome-bio-agent-skills200—~1.2kAutomated safety check: NotesMIT
Web Research Search Tipsmalob/nix-config463—~2.4kAutomated safety check: PassMIT
Exa SearchK-Dense-AI/scientific-agent-skills48k1 repos~1.6kAutomated safety check: NotesMIT
Exa SearchAI4Scientist/nano-scientist1282 repos~1.8kAutomated safety check: NotesNone

Similar skills

  • Deep Science Writer

    CYC2002tommy/Deep-Research-Agent

    End-to-end scientific research pipeline combining Exa Search, Playwright, deep-research, text-humanization, and iterative Remi peer review.

    311 GitHub stars~8.7k tokensUpdated 1 mo ago
    Research & ScienceAuto-check: warnings

  • Exa Search

    BioTender-max/awesome-bio-agent-skills

    Web toolkit powered by Exa, tuned for scientific and technical content.

    200 GitHub stars~1.2k tokensUpdated 3 mo ago
    Research & ScienceAuto-check: notes

  • Web Research Search Tips

    malob/nix-config

    Practical guidance for multi-source web research with Exa, the Firecrawl CLI and Reddit MCP tools: when to search, when to fetch and which tool to prefer.

    463 GitHub stars~2.4k tokensUpdated today
    Research & ScienceAuto-check passed

  • Exa Search

    K-Dense-AI/scientific-agent-skills

    Searches scientific and technical web content with Exa and extracts page or PDF text from URLs in batches.

    48k GitHub starsUsed in 1 repo~1.6k tokens
    Research & ScienceAuto-check: notes

  • Exa Search

    AI4Scientist/nano-scientist

    AI-powered web search via Exa with content extraction. An agent skill from AI4Scientist/nano-scientist.

    128 GitHub starsUsed in 2 repos~1.8k tokens
    Research & ScienceAuto-check: notes

  • AI RAG Pipeline

    NeverSight/learn-skills.dev

    Build RAG (Retrieval Augmented Generation) pipelines with web search and LLMs.

    217 GitHub starsUsed in 1 repo~2k tokens
    AI & LLM EngineeringAuto-check passed

More from affaan-m/ECC

All 682 skills in this repo

  • Skill Stocktake

    affaan-m/ECC

    Audits your installed Claude skills and commands for quality, with a quick mode for recently changed skills and a full mode that evaluates all of them through subagents.

    277k GitHub starsUsed in 5 repos~3.1k tokens
    Auto-check passed

  • VideoDB Video Search and Editing

    affaan-m/ECC

    Ingests, indexes, searches, edits and monitors video, audio and live streams through the VideoDB Python SDK, returning stream links, clips and timestamps.

    277k GitHub starsUsed in 3 repos~3.5k tokens
    Auto-check: notes

  • Docs Governance

    affaan-m/ECC

    Route broad documentation-governance requests to existing ECC skills and run an opt-in, read-only audit of mapped documentation roles, links, ADR indexes, and evidence references.

    277k GitHub stars~1.1k tokensUpdated today
    Auto-check passed

  • Rules Distillation

    affaan-m/ECC

    Scans installed skills for principles that recur across them and proposes rule-file changes: append, revise, add a section, create a file or leave as covered.

    277k GitHub starsUsed in 2 repos~2.3k tokens
    Auto-check passed

  • Master Agreement Generator

    affaan-m/ECC

    Builds DRAFT counterparty agreements from one markdown template and a small JSON spec per party, with clauses picked by the party's role.

    277k GitHub stars~2.9k tokensUpdated today
    Auto-check passed

  • Frontend Design Direction

    affaan-m/ECC

    Set an ECC-specific frontend design direction for production UI work.

    277k GitHub starsUsed in 1 repo~2.2k tokens
    Auto-check passed

Works with

Categories

Questions about Research Ops

What does Research Ops do?

Evidence-first current-state research workflow for ECC. An agent skill from affaan-m/ECC. Research Ops is an agent skill from affaan-m/ECC. Evidence-first current-state research workflow for ECC.

When should I use Research Ops?

Research Ops fits situations like: the user wants fresh facts; A recommendation built from current public evidence and any supplied local context.

How do I install Research Ops in Claude Code?

Run `npx skills add affaan-m/ECC --skill research-ops -a claude-code`. Or copy the skill folder (skills/research-ops in affaan-m/ECC) into .claude/skills/research-ops in your project. Claude Code loads it when a task matches its description.

How do I install Research Ops in Codex?

Run `npx skills add affaan-m/ECC --skill research-ops -a codex`. Or copy the skill folder (skills/research-ops in affaan-m/ECC) into .agents/skills/research-ops in your project. Codex loads it when a task matches its description.

Can I use Research Ops 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 affaan-m/ECC --skill research-ops -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-ops, .gemini/skills/research-ops, .github/skills/research-ops and .opencode/skills/research-ops in your project.

What does Research Ops need to run?

SKILL.md names no scripts, command-line tools or credentials: Research Ops is instructions for the agent only.

Does Research Ops access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Research Ops 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 Research Ops use?

Research Ops is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Research Ops use?

About 902 tokens (SKILL.md is roughly 3.6k 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 Research Ops?

Skills that share tags, products or a category with Research Ops: Deep Science Writer (CYC2002tommy/Deep-Research-Agent, 311 stars), Exa Search (BioTender-max/awesome-bio-agent-skills, 200 stars), Web Research Search Tips (malob/nix-config, 463 stars) and Exa Search (K-Dense-AI/scientific-agent-skills, 48k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research Ops?

affaan-m (a GitHub user) maintains it in affaan-m/ECC, which has 276,673 GitHub stars. The repository holds 683 skills in this directory. The repository was last updated on October 11, 2026.

Source: affaan-m/ECC on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.