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Vendored deer-flow upstream (bytedance/deer-flow) plus prompt-injection hardening: - New deerflow.security package: content_delimiter, html_cleaner, sanitizer (8 layers — invisible chars, control chars, symbols, NFC, PUA, tag chars, horizontal whitespace collapse with newline/tab preservation, length cap) - New deerflow.community.searx package: web_search, web_fetch, image_search backed by a private SearX instance, every external string sanitized and wrapped in <<<EXTERNAL_UNTRUSTED_CONTENT>>> delimiters - All native community web providers (ddg_search, tavily, exa, firecrawl, jina_ai, infoquest, image_search) replaced with hard-fail stubs that raise NativeWebToolDisabledError at import time, so a misconfigured tool.use path fails loud rather than silently falling back to unsanitized output - Native client back-doors (jina_client.py, infoquest_client.py) stubbed too - Native-tool tests quarantined under tests/_disabled_native/ (collect_ignore_glob via local conftest.py) - Sanitizer Layer 7 fix: only collapse horizontal whitespace, preserve newlines and tabs so list/table structure survives - Hardened runtime config.yaml references only the searx-backed tools - Factory overlay (backend/) kept in sync with deer-flow tree as a reference / source See HARDENING.md for the full audit trail and verification steps.
1.8 KiB
1.8 KiB
Output Patterns
Use these patterns when skills need to produce consistent, high-quality output.
Template Pattern
Provide templates for output format. Match the level of strictness to your needs.
For strict requirements (like API responses or data formats):
## Report structure
ALWAYS use this exact template structure:
# [Analysis Title]
## Executive summary
[One-paragraph overview of key findings]
## Key findings
- Finding 1 with supporting data
- Finding 2 with supporting data
- Finding 3 with supporting data
## Recommendations
1. Specific actionable recommendation
2. Specific actionable recommendation
For flexible guidance (when adaptation is useful):
## Report structure
Here is a sensible default format, but use your best judgment:
# [Analysis Title]
## Executive summary
[Overview]
## Key findings
[Adapt sections based on what you discover]
## Recommendations
[Tailor to the specific context]
Adjust sections as needed for the specific analysis type.
Examples Pattern
For skills where output quality depends on seeing examples, provide input/output pairs:
## Commit message format
Generate commit messages following these examples:
**Example 1:**
Input: Added user authentication with JWT tokens
Output:
feat(auth): implement JWT-based authentication
Add login endpoint and token validation middleware
**Example 2:**
Input: Fixed bug where dates displayed incorrectly in reports
Output:
fix(reports): correct date formatting in timezone conversion
Use UTC timestamps consistently across report generation
Follow this style: type(scope): brief description, then detailed explanation.
Examples help Claude understand the desired style and level of detail more clearly than descriptions alone.