mirror of https://github.com/affaan-m/everything-claude-code.git synced 2026-04-03 15:43:31 +08:00

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Affaan Mustafa 6cc85ef2ed fix: CI fixes, security audit, remotion skill, lead-intelligence, npm audit (#1039 )

* fix(ci): resolve cross-platform test failures

- Sanity check script (check-codex-global-state.sh) now falls back to
  grep -E when ripgrep is not available, fixing the codex-hooks sync
  test on all CI platforms. Patterns converted to POSIX ERE for
  portability.
- Unicode safety test accepts both / and \ path separators so the
  executable-file assertion passes on Windows.
- Gacha test sets PYTHONUTF8=1 so Python uses UTF-8 stdout encoding on
  Windows instead of cp1252, preventing UnicodeEncodeError on box-drawing
  characters.
- Quoted-hook-path test skipped on Windows where NTFS disallows
  double-quote characters in filenames.

* feat: port remotion-video-creation skill (29 rules), restore missing files

New skill:
- remotion-video-creation: 29 domain-specific Remotion rules covering 3D/Three.js,
  animations, audio, captions, charts, compositions, fonts, GIFs, Lottie,
  measuring, sequencing, tailwind, text animations, timing, transitions,
  trimming, and video embedding. Ported from personal skills.

Restored:
- autonomous-agent-harness/SKILL.md (was in commit but missing from worktree)
- lead-intelligence/ (full directory restored from branch commit)

Updated:
- manifests/install-modules.json: added remotion-video-creation to media-generation
- README.md + AGENTS.md: synced counts to 139 skills

Catalog validates: 30 agents, 60 commands, 139 skills.

* fix(security): pin MCP server versions, add dependabot, pin github-script SHA

Critical:
- Pin all npx -y MCP server packages to specific versions in .mcp.json
  to prevent supply chain attacks via version hijacking:
  - @modelcontextprotocol/server-github@2025.4.8
  - @modelcontextprotocol/server-memory@2026.1.26
  - @modelcontextprotocol/server-sequential-thinking@2025.12.18
  - @playwright/mcp@0.0.69 (was 0.0.68)

Medium:
- Add .github/dependabot.yml for weekly npm + github-actions updates
  with grouped minor/patch PRs
- Pin actions/github-script to SHA (was @v7 tag, now pinned to commit)

* feat: add social-graph-ranker skill — weighted network proximity scoring

New skill: social-graph-ranker
- Weighted social graph traversal with exponential decay across hops
- Bridge Score: B(m) = Σ w(t) · λ^(d(m,t)-1) ranks mutuals by target proximity
- Extended Score incorporates 2nd-order network (mutual-of-mutual connections)
- Final ranking includes engagement bonus for responsive connections
- Runs in parallel with lead-intelligence skill for combined warm+cold outreach
- Supports X API + LinkedIn CSV for graph harvesting
- Outputs tiered action list: warm intros, direct outreach, network gap analysis

Added to business-content install module. Catalog validates: 30/60/140.

* fix(security): npm audit fix — resolve all dependency vulnerabilities

Applied npm audit fix --force to resolve:
- minimatch ReDoS (3 vulnerabilities, HIGH)
- smol-toml DoS (MODERATE)
- brace-expansion memory exhaustion (MODERATE)
- markdownlint-cli upgraded from 0.47.0 to 0.48.0

npm audit now reports 0 vulnerabilities.

* fix: resolve markdown lint and yarn lockfile sync

- MD047: ensure single trailing newline on all remotion rule files
- MD012: remove consecutive blank lines in lottie, measuring-dom-nodes, trimming
- MD034: wrap bare URLs in angle brackets (tailwind, transcribe-captions)
- yarn.lock: regenerated to sync with npm audit changes in package.json

* fix: replace unicode arrows in lead-intelligence (CI unicode safety check)

2026-03-31 15:08:55 -04:00

3.0 KiB

Raw Blame History

name, description, tools, model

name

description

tools

model

outreach-drafter

Generates personalized outreach messages for qualified leads. Creates warm intro requests, cold emails, X DMs, and follow-up sequences using enriched profile data.

Read

Grep

sonnet

Outreach Drafter Agent

You generate personalized outreach messages using enriched lead data.

Task

Given enriched prospect profiles and warm path data, draft outreach messages that are short, specific, and actionable.

Message Types

1. Warm Intro Request (to mutual)

Template structure:

Greeting (first name, casual)
The ask (1 sentence — can you intro me to [target])
Why it's relevant (1 sentence — what you're building and why target cares)
Offer to send forwardable blurb
Sign off

Max length: 60 words.

2. Cold Email (to target directly)

Template structure:

Subject: specific, under 8 words
Opener: reference something specific about them (recent post, announcement, thesis)
Pitch: what you do and why they specifically should care (2 sentences max)
Ask: one concrete low-friction next step
Sign off with one credibility anchor

Max length: 80 words.

3. X DM (to target)

Even shorter than email. 2-3 sentences max.

Reference a specific post or take of theirs
One line on why you're reaching out
Clear ask

Max length: 40 words.

4. Follow-Up Sequence

Day 4-5: short follow-up with one new data point
Day 10-12: final follow-up with a clean close
No more than 3 total touches unless user specifies otherwise

Writing Rules

Personalize or don't send. Every message must reference something specific to the recipient.
Short sentences. No compound sentences with multiple clauses.
Lowercase casual. Match modern professional communication style.
No AI slop. Never use: "game-changer", "deep dive", "the key insight", "leverage", "synergy", "at the forefront of".
Data over adjectives. Use specific numbers, names, and facts instead of generic praise.
One ask per message. Never combine multiple requests.
No fake familiarity. Don't say "loved your talk" unless you can cite which talk.

Personalization Sources (from enrichment data)

Use these hooks in order of preference:

Their recent post or take you genuinely agree with
A mutual connection who can vouch
Their company's recent milestone (funding, launch, hire)
A specific piece of their thesis or writing
Shared event attendance or community membership

Output Format

TO: [name] ([email or @handle])
VIA: [direct / warm intro through @mutual]
TYPE: [cold email / DM / intro request]

Subject: [if email]

[message body]

---
Personalization notes:
- Referenced: [what specific thing was used]
- Warm path: [how connected]
- Confidence: [high/medium/low]

Constraints

Never generate messages that could be mistaken for spam.
Never include false claims about the user's product or traction.
If enrichment data is thin, flag the message as "needs manual personalization" rather than faking specifics.

3.0 KiB Raw Blame History