Agent skill

Spark Recipe Meeting Prep

by readdle in readdle/spark-cli-skills

Prepare for an upcoming meeting: check agenda, search for email context, look up attendee details, and flag open threads that should be raised.

MITAuto-check passedSales & Support

Install Spark Recipe Meeting Prep

skills CLI
$ npx skills add readdle/spark-cli-skills --skill spark-recipe-meeting-prep -a claude-code

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

GitHub CLI
$ gh skill install readdle/spark-cli-skills spark-recipe-meeting-prep --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/readdle/spark-cli-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/recipe-meeting-prep .claude/skills/spark-recipe-meeting-prep && 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
spark-recipe-meeting-prep
GitHub stars
149
Token cost
~994 tokens
SKILL.md length
464 words
Files
1
Skills in repo
34
Repo updated
First seen
Licence
MIT

At a glance

Prepare for an upcoming meeting: check agenda, search for email context, look up attendee details, and flag open threads that should be raised.

  • Works in 7 steps: Check the calendar → Search for relevant email context → Look up attendees → …
  • Tasks that involve Sales call preparation
  • SKILL.md covers Steps and Tips
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Spark Recipe Meeting Prep is an agent skill from readdle/spark-cli-skills. Prepare for an upcoming meeting: check agenda, search for email context, look up attendee details, and flag open threads that should be raised.

Its SKILL.md is about 990 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 Sales & Support, covering Sales call preparation. The licence is MIT.

When your agent uses it

  • Tasks that involve Sales call preparation

Example prompts

  • “/spark-recipe-meeting-prep”

Workflow steps

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

  1. Check the calendar
  2. Search for relevant email context
  3. Look up attendees
  4. Check recent correspondence with attendees
  5. Flag unresolved threads to raise in the meeting
  6. Present the prep summary
  7. (optional, post-meeting): Meeting–email gap analysis

What it can do on your machine

Read from SKILL.md and the folder at commit cb20383. 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 (its code samples are bash).

    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

Spark Recipe Meeting Prep loads about 994 tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 464 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~994

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 readdle/spark-cli-skills at commit cb20383, republished under its MIT licence (© readdle). 464 words, ~994 tokens.

Download SKILL.mdSave it as .claude/skills/spark-recipe-meeting-prep/SKILL.md (or your agent's skills folder).
name
spark-recipe-meeting-prep
description
Prepare for an upcoming meeting: check agenda, search for email context, look up attendee details, and flag open threads that should be raised.
metadata.version
1.0.0

Recipe: Meeting Prep

Prepare for an upcoming meeting by gathering calendar context, relevant email threads, and attendee information. Optionally, run a gap analysis after the meeting to flag verbal commitments without a written trail and open threads that weren't raised.

Prerequisite: Read the use-spark base skill for command reference and filter syntax.

Access level required: read-only.

Steps

Step 1: Check the calendar
bash
spark events --today

Identify the meeting to prepare for - note the topic, time, and attendees.

Step 2: Search for relevant email context
bash
spark search "meeting topic or project name"

This returns up to 20 emails with full bodies, sorted by relevance. Read the most relevant threads for context.

Step 3: Look up attendees
bash
spark contacts "attendee name"

Repeat for each attendee to gather their email and any other details.

Step 4: Check recent correspondence with attendees
bash
spark emails --filter "from:attendee@co.com newer_than:14d"

Review any recent threads with the meeting participants for open items or unanswered questions.

Step 5: Flag unresolved threads to raise in the meeting

Check for open or unreplied threads with the attendees that may be worth bringing up:

bash
spark emails --filter "from:attendee@co.com is:unreplied newer_than:14d"
spark emails --filter "to:attendee@co.com is:unreplied newer_than:14d"

Note any threads that look relevant to the meeting topic but haven't been resolved — these are candidates to raise during the discussion.

Step 6: Present the prep summary

Summarize for the user:

  • Meeting: time, title, attendees
  • Context: key points from relevant email threads
  • Open items: unanswered questions or pending actions from recent correspondence
  • Threads to raise: unreplied or unresolved threads with attendees that relate to the meeting topic
  • Attendees: contact details for reference
Show full SKILL.md (240 more words)Show less
Step 7 (optional, post-meeting): Meeting–email gap analysis

After the meeting, compare what was discussed against the email record to catch gaps. This step requires the meeting transcript to be available.

  1. Read the transcript:

    bash
    spark meeting <id> --transcript --notes

    Extract topics discussed, commitments made, and decisions reached.

  2. For each major topic, check whether it has an email trail:

    bash
    spark search "topic from meeting"
  3. Flag two kinds of gaps:

    Discussed in meeting, no email trail — verbal commitments or decisions that may need a follow-up email to create a written record.

    Open email threads not raised in meeting — compare the unreplied threads from Step 5 against what was actually discussed. Flag any that seem relevant but weren't mentioned.

    Present gaps neutrally — not every gap needs action. Some things are intentionally verbal-only, and some threads are intentionally deferred.

Tips

  • Run this 15-30 minutes before the meeting for fresh context.
  • Use spark search rather than spark emails for topic-based context - search returns full bodies.
  • If the meeting is recurring, check spark meetings --filter "subject:meeting-topic" for past transcripts.
  • For large meetings, focus on the 2-3 most important attendees rather than looking up everyone.
  • The is:unreplied filter is especially useful for surfacing threads that may have been forgotten — both before the meeting (things to raise) and after (things that were missed).
  • For recurring meetings, running the post-meeting gap analysis regularly can reveal patterns where the same threads go unaddressed week after week.

© readdle, 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/recipe-meeting-prep of readdle/spark-cli-skills.

Open the folder on GitHubat commit cb20383

Compare with similar skills

Spark Recipe Meeting Prep 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.

Spark Recipe Meeting Prep compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Spark Recipe Meeting Prep this skillreaddle/spark-cli-skills149—~994Automated safety check: PassMIT
Luopan Company Researchzhangxiaoqiang1991/luopan389—~998Automated safety check: PassMIT
Company Researchstophobia/deerflow2.0-enhanced822—~845Automated safety check: PassMIT
Meeting Prep BriefBrianRWagner/ai-marketing-claude-code-skills441—~922Automated safety check: PassNone
SdtStopDisTrain/sdt-skills309—~535Automated safety check: PassMIT
Account Researchextruct-ai/gtm-skills109—~1.6kAutomated safety check: PassNone

Similar skills

  • Luopan Company Research

    zhangxiaoqiang1991/luopan

    罗盘的公司研究子模式。研究具体上市或非上市公司的财务增长、商业模式、 竞争生态位、治理与组织信号,并分别生成投资初筛和求职初筛。

    389 GitHub stars~998 tokensUpdated 2 mo ago
    Sales & SupportAuto-check passed
  • Company Research

    stophobia/deerflow2.0-enhanced

    综合企业背景调研技能,用于尽职调查、合作伙伴评估、投资分析、市场研究等场景。支持公司工商信息、财务数据、法律风险、舆情分析、竞品对比等多维度调研,自动生成Markdown和HTML格式的专业调研报告。触发条件:用户提及"企业调研"、"公司背景"、"尽职调查"、"合作伙伴评估"、"投资分析"、"市场研究"等关键词。

    822 GitHub stars~845 tokensUpdated 6 mo ago
    Sales & SupportAuto-check passed
  • Meeting Prep Brief

    BrianRWagner/ai-marketing-claude-code-skills

    Builds a pre-meeting brief from your Obsidian vault: participant research, past notes, open commitments, a prioritized agenda and sharp questions.

    441 GitHub stars~922 tokensUpdated 6 mo ago
    Sales & SupportAuto-check passed
  • Sdt

    StopDisTrain/sdt-skills

    SDT 内容生产工具箱的总入口:根据当前任务选择最合适的 sdt- 模块,既能完成标题、开头等单一步骤,也能组织从账号研究到发布的完整流程。用户不知道该用哪个 SDT Skill,或希望一站式完成内容生产时使用。

    309 GitHub stars~535 tokensUpdated 1 mo ago
    Sales & SupportAuto-check passed
  • Account Research

    extruct-ai/gtm-skills

    Deep-research a single target account into a decision-ready dossier: the entity tree, the buying units and decision-makers, live signals (open/closed roles, leadership moves, news, tech stack), and…

    109 GitHub stars~1.6k tokensUpdated 12 days ago
    Sales & SupportAuto-check passed
  • Call Prep

    breakstageaxe61/genspark-claw

    Prepare an AI phone call end-to-end — research the callee, set a concrete objective and fallback, draft a natural call script with branching, and produce a post-call summary template.

    169 GitHub stars~986 tokensUpdated 15 days ago
    Sales & SupportAuto-check passed

More from readdle/spark-cli-skills

All 34 skills in this repo
  • Spark Persona Exec Assistant

    readdle/spark-cli-skills

    Executive assistant persona for Spark. An agent skill from readdle/spark-cli-skills.

    149 GitHub stars~775 tokensUpdated 4 days ago
    Auto-check passed
  • Spark Persona Founder

    readdle/spark-cli-skills

    Founder / CEO persona for Spark. An agent skill from readdle/spark-cli-skills.

    149 GitHub stars~1.1k tokensUpdated 4 days ago
    Auto-check passed
  • Use Spark

    readdle/spark-cli-skills

    Use the spark CLI to access the user's Spark email data - list emails, search by topic, read threads, check calendar events, find availability, look up contacts, and view team info.

    149 GitHub stars~14k tokensUpdated 4 days ago
    Auto-check: warnings
  • Spark Persona Freelancer

    readdle/spark-cli-skills

    Freelancer / solo operator persona for Spark. An agent skill from readdle/spark-cli-skills.

    149 GitHub stars~1.1k tokensUpdated 4 days ago
    Auto-check passed
  • Spark Persona Meeting Manager

    readdle/spark-cli-skills

    Meeting manager persona for Spark. An agent skill from readdle/spark-cli-skills.

    149 GitHub stars~1.2k tokensUpdated 4 days ago
    Auto-check passed
  • Spark Persona Project Manager

    readdle/spark-cli-skills

    Project manager persona for Spark. An agent skill from readdle/spark-cli-skills.

    149 GitHub stars~1.3k tokensUpdated 4 days ago
    Auto-check passed

Categories

Questions about Spark Recipe Meeting Prep

What does Spark Recipe Meeting Prep do?

Prepare for an upcoming meeting: check agenda, search for email context, look up attendee details, and flag open threads that should be raised. Spark Recipe Meeting Prep is an agent skill from readdle/spark-cli-skills. Prepare for an upcoming meeting: check agenda, search for email context, look up attendee details, and flag open threads that should be raised.

When should I use Spark Recipe Meeting Prep?

Spark Recipe Meeting Prep fits situations like: tasks that involve Sales call preparation.

How do I install Spark Recipe Meeting Prep in Claude Code?

Run `npx skills add readdle/spark-cli-skills --skill spark-recipe-meeting-prep -a claude-code`. Or copy the skill folder (skills/recipe-meeting-prep in readdle/spark-cli-skills) into .claude/skills/spark-recipe-meeting-prep in your project. Claude Code loads it when a task matches its description.

How do I install Spark Recipe Meeting Prep in Codex?

Run `npx skills add readdle/spark-cli-skills --skill spark-recipe-meeting-prep -a codex`. Or copy the skill folder (skills/recipe-meeting-prep in readdle/spark-cli-skills) into .agents/skills/spark-recipe-meeting-prep in your project. Codex loads it when a task matches its description.

Can I use Spark Recipe Meeting Prep 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 readdle/spark-cli-skills --skill spark-recipe-meeting-prep -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/spark-recipe-meeting-prep, .gemini/skills/spark-recipe-meeting-prep, .github/skills/spark-recipe-meeting-prep and .opencode/skills/spark-recipe-meeting-prep in your project.

What does Spark Recipe Meeting Prep need to run?

SKILL.md names no scripts, command-line tools or credentials: Spark Recipe Meeting Prep is instructions for the agent only.

Does Spark Recipe Meeting Prep 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 Spark Recipe Meeting Prep 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 Spark Recipe Meeting Prep use?

Spark Recipe Meeting Prep 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 Spark Recipe Meeting Prep use?

About 994 tokens (SKILL.md is roughly 4k 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 Spark Recipe Meeting Prep?

Skills that share tags, products or a category with Spark Recipe Meeting Prep: Luopan Company Research (zhangxiaoqiang1991/luopan, 389 stars), Company Research (stophobia/deerflow2.0-enhanced, 822 stars), Meeting Prep Brief (BrianRWagner/ai-marketing-claude-code-skills, 441 stars) and Sdt (StopDisTrain/sdt-skills, 309 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Spark Recipe Meeting Prep?

readdle (a GitHub organization) maintains it in readdle/spark-cli-skills, which has 149 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on October 7, 2026.

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