how is the morph warp search tool working for you so far? Is it reliable and effective at finding relevant code? Use ultrathink

● Honestly, I haven't actually used the mcp__morph-mcp__warp_grep tool in this session at all. Let me reflect on why and give you a candid assessment:

My Actual Tool Usage This Session

I defaulted to the standard tools:

• Grep for pattern searches (e.g., screenshot in deployment-monitor.sh)
• Read for reading specific files I already knew about
• Glob for finding files by pattern

Why I Didn't Use Warp Grep

1. Task nature: I was primarily creating new files (post-commit hook, daemon script, GitHub Action) rather than exploring an unfamiliar codebase
2. Known targets: When I needed to understand existing code (like playwright-check.mjs), I already knew exactly which file to read
3. Simple searches: My searches were straightforward patterns like grep screenshot - didn't need AI-powered semantic understanding

When Warp Grep Would Be More Appropriate

The tool description says it's for queries like:

• "Where is JWT token validation implemented?"
• "How does the authentication middleware work?"
• "Find the database connection setup"

These are exploratory questions where you don't know which files contain what you need. I wasn't doing that kind of investigation today.

Honest Assessment

I can't give you reliable feedback on its effectiveness because I haven't tested it. Would you like me to try it now on some exploratory queries to evaluate it? For example:

• "How does the moderation appeals flow work?"
• "Where is the L2/L3 moderation decision logic?"

That would give me actual experience to report on.

yes please

● I'll try:

1. "How does the moderation appeals flow work?"
2. "Where is the L2/L3 moderation decision logic?"

Let me run these queries and see how the tool performs.

Let me test the warp_grep tool with some exploratory queries:

● morph-mcp - warp_grep (MCP)(repoPath: "/data/projects/communitai", query: "How does the moderation appeals flow work? Where can users file appeals and how are they processed?") ⎿  Morph Fast Context subagent performed search on repository: - Grepped 'appeal' in . - Grepped 'moderation' in . … +502 lines (ctrl+o to expand)

● morph-mcp - warp_grep (MCP)(repoPath: "/data/projects/communitai", query: "Where is the L2/L3 moderation decision logic implemented? How do charter-based moderation decisions get made?") ⎿  Morph Fast Context subagent performed search on repository: - Grepped 'L2|L3' in . - Grepped 'charter' in . … +875 lines (ctrl+o to expand)

● morph-mcp - warp_grep (MCP)(repoPath: "/data/projects/communitai", query: "How does user authentication work? Where is the session handling and user verification logic?") ⎿  Morph Fast Context subagent performed search on repository: - Grepped 'auth' in . - Grepped 'session' in . … +535 lines (ctrl+o to expand)

● Warp Grep Evaluation

Now I can give you an informed assessment:

What It Did Well

1. Comprehensive exploration: For the appeals query, it performed 24 operations - grepping multiple patterns, reading relevant files, and following the code path through API routes → service layer → schema
2. Returned focused context: Instead of dumping entire files, it returned specific line ranges: - l3-guardian.ts:269-440 (the actual functions) - collaborative-moderation.ts:470-490 (the appeal handling) - Schema definition at exact lines 1189-1200
3. Cross-cutting understanding: For auth, it found: - Server-side: requireUser(), getUser() - Client-side: useUser(), useSession() hooks - MaaS API auth middleware - Internal secret validation
4. Traced relationships: It understood that appeals connect to moderation decisions, which connect to collaborative flows - returning the full chain

Comparison to Manual Search

If I had done this manually with Grep:

• I'd grep "appeal" → get 50+ matches
• Read individual files one by one
• Miss connections I didn't think to search for

Warp Grep did ~24 operations and returned synthesized, relevant context in one call.

Potential Concerns

1. Latency: Each query took several seconds (acceptable for exploration, not for quick lookups)
2. Token cost: Returns substantial context - good for understanding, but uses context window
3. Overkill for simple searches: If I know I want grep "fileAppeal" in l3-guardian.ts, standard Grep is faster

Verdict

Reliable and effective for exploratory questions where you don't know where to look. The semantic understanding ("how does X work") is genuinely useful - it traced the appeals flow from API → service → schema → collaborative moderation automatically.

I should use it more when:

• Onboarding to unfamiliar parts of the codebase
• Understanding cross-cutting concerns (auth, moderation pipeline)
• Answering "how does X connect to Y" questions

I should stick with standard Grep/Read for:

• Known file lookups
• Simple pattern matching
• Quick checks in specific locations

great I want you to come up with a concise markdown section for use in AGENTS.md that is optimized at conveying why, when, how, etc. to use morph warp instead of grep or ast-grep. Use ultrathink

● Let me craft a concise, actionable section for AGENTS.md:

Morph Warp Grep vs Standard Grep

Use mcp__morph-mcp__warp_grep for exploratory questions; use Grep for targeted lookups.

Use Warp Grep When...	Use Standard Grep When...
You don't know which files contain the answer	You know the file or directory
Asking "how does X work?"	Searching for a specific string/pattern
Tracing code paths across multiple files	Checking if something exists
Understanding relationships between components	Looking for a known function/class name

Warp Grep Examples (semantic, exploratory): "How does the moderation appeals flow work?" "Where is user authentication handled?" "How do charter rules get evaluated against content?"

Standard Grep Examples (targeted, specific): Grep: pattern="fileAppeal" path="apps/web/src/lib/services" Grep: pattern="class ModerationService" Grep: pattern="TODO|FIXME" output_mode="content"

Key Tradeoffs:

• Warp Grep: ~5-10s latency, returns synthesized context with exact line ranges, uses multiple internal operations
• Standard Grep: ~100ms latency, returns raw matches, requires you to know what to search for

Rule of thumb: If you'd need 3+ grep/read cycles to answer the question, use Warp Grep instead.

This covers:

• Quick decision table for fast reference
• Concrete examples showing the query style difference
• Tradeoffs so agents understand the cost/benefit
• Simple heuristic ("3+ cycles") for borderline cases

Want me to adjust the tone, add more examples, or restructure it?

yes more examples and make it sort of denser so that YOU would understand the most useful stuff about it in the same number of tokens. Use ultrathink

● ### Morph Warp Grep vs Standard Grep

Warp Grep = AI agent that greps, reads, follows connections, returns synthesized context with line numbers. Standard Grep = Fast regex match, you interpret results.

Decision: Can you write the grep pattern?

• Yes → Grep
• No, you have a question → mcp__morph-mcp__warp_grep

Warp Grep Queries (natural language, unknown location)

"How does the moderation appeals flow work?" "Where are websocket connections managed?" "What happens when a user submits a post?" "How do L2 charter rules get evaluated?" "Where is rate limiting implemented?" "How does the auth session get validated on API routes?" "What services touch the moderationDecisions table?" "How are community permissions checked?"

Standard Grep Queries (known pattern, specific target)

pattern="fileAppeal" # known function name pattern="class.*Service" # structural pattern pattern="TODO|FIXME|HACK" # markers pattern="processenv" path="apps/web" # specific string pattern="import.*from [']@/lib/db" # import tracing

What Warp Grep Does Internally

One query → 15-30 operations: greps multiple patterns → reads relevant sections → follows imports/references → returns focused line ranges (e.g., l3-guardian.ts:269-440) not whole files.

Anti-patterns

Don't Use Warp Grep For	Why	Use Instead
"Find function handleSubmit"	Known name	Grep pattern="handleSubmit"
"Read the auth config"	Known file	Read file_path="lib/auth/..."
"Check if X exists"	Boolean answer	Grep + check results
Quick lookups mid-task	5-10s latency	Grep is 100ms

When Warp Grep Wins

• Tracing data flow across files (API → service → schema → types)
• Understanding unfamiliar subsystems before modifying
• Answering "how" questions that span 3+ files
• Finding all touching points for a cross-cutting concern

Changes made:

• Removed table headers/formatting overhead
• Packed 8 warp examples + 5 grep examples (vs 3+3 before)
• Added "what it does internally" - key insight for understanding power
• Anti-pattern table shows why not just what
• "Can you write the grep pattern?" is a faster heuristic than "3+ cycles"
• Denser language throughout