* test(skills): add trigger eval set for systematic-literature-review skill
20 eval queries (10 should-trigger, 10 should-not-trigger) for use with
skill-creator's run_eval.py. Includes real-world SLR queries contributed
by @VANDRANKI (issue #1862 author) and edge cases for routing
disambiguation with academic-paper-review.
* test(skills): add grader expectations for SLR skill evaluation
5 eval cases with 39 expectations covering:
- Standard SLR flow (APA/BibTeX/IEEE format selection)
- Keyword extraction and search behavior
- Subagent dispatch for metadata extraction
- Report structure (themes, convergences, gaps, per-paper annotations)
- Negative case: single-paper routing to academic-paper-review
- Edge case: implicit SLR without explicit keywords
* refactor(skills): shorten SLR description for better trigger rate
Reduce description from 833 to 344 chars. Key changes:
- Lead with "systematic literature review" as primary trigger phrase
- Strengthen single-paper exclusion: "Not for single-paper tasks"
- Remove verbose example patterns that didn't improve routing
Tested with run_eval.py (10 runs/query):
- False positive "best paper on RL": 67% → 20% (improved)
- True positive explicit SLR query: ~30% (unchanged)
Low recall is a routing-layer limitation, not a description issue —
see PR description for full analysis.
* Potential fix for pull request finding
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
* feat(skills): add systematic-literature-review skill for multi-paper SLR workflows
Adds a new skill that produces a structured systematic literature review (SLR)
across multiple academic papers on a topic. Addresses #1862 with a pure skill
approach: no new tools, no architectural changes, no new dependencies.
Skill layout:
- SKILL.md — 4+1 phase workflow (plan, search, extract, synthesize, present)
- scripts/arxiv_search.py — arXiv API client, stdlib only, with a
requests->urllib fallback shim modeled after github-deep-research's
github_api.py
- templates/{apa,ieee,bibtex}.md — citation format templates selected
dynamically in Phase 4, mirroring podcast-generation's templates/ pattern
Design notes:
- Multi-paper synthesis uses the existing `task` tool to dispatch extraction
subagents in parallel. SKILL.md's Phase 3 includes a fixed decision table
for batch splitting to respect the runtime's MAX_CONCURRENT_SUBAGENTS = 3
cap, and explicitly tells the agent to strip the "Task Succeeded. Result: "
prefix before parsing subagent JSON output.
- arXiv only, by design. Semantic Scholar and PubMed adapters would push the
scope toward a standalone MCP server (see #933) and are intentionally out
of scope for this skill.
- Coexists with the existing `academic-paper-review` skill: this skill does
breadth-first synthesis across many papers, academic-paper-review does
single-paper peer review. The two are routed via distinct triggers and
can compose (SLR on many + deep review on 1-2 important ones).
- Hard upper bound of 50 papers, tied to the Phase 3 concurrency strategy.
Larger surveys degrade in synthesis quality and are better split by
sub-topic.
BibTeX template explicitly uses @misc for arXiv preprints (not @article),
which is the most common mistake when generating BibTeX for arXiv papers.
arxiv_search.py was smoke-tested end-to-end against the live arXiv API with
two query shapes (relevance sort, submittedDate sort with category filter);
all returned JSON fields parse correctly (id normalization, Atom namespace
handling, URL encoding for multi-word queries).
* fix(skills): prevent LLM from saving intermediate search results to file
Adds an explicit "do not save" instruction at the end of Phase 2.
Observed during Test 1 with DeepSeek: the model saved search results
to a markdown file before proceeding to Phase 3, wasting 2-3 tool call
rounds and increasing the risk of hitting the graph recursion limit.
The search JSON should stay in context for Phase 3, not be persisted.
* fix(skills): use relevance+start-date instead of submittedDate sorting
Test 2 revealed that arXiv's submittedDate sorting returns the most
recently submitted papers in the category regardless of query relevance.
Searching "diffusion models" with sortBy=submittedDate in cs.CV returned
papers on spatial memory, Navier-Stokes, and photon-counting CT — none
about diffusion models. The LLM then retried with 4 different queries,
wasting tool calls and approaching the recursion limit.
Fix: always sort by relevance; when the user wants "recent" papers,
combine relevance sorting with --start-date to constrain the time window.
Also add an explicit "run the search exactly once" instruction to prevent
the retry loop.
* fix(skills): wrap multi-word arXiv queries in double quotes for phrase matching
Without quotes, `all:diffusion model` is parsed by arXiv's Lucene as
`all:diffusion OR model`, pulling in unrelated papers from physics
(thermal diffusion) and other fields. Wrapping in double quotes forces
phrase matching: `all:"diffusion model"`.
Also fixes date filtering: the previous bug caused 2011 papers to appear
in results despite --start-date 2024-04-09, because the unquoted query
words were OR'd with the date constraint.
Verified: "diffusion models" --category cs.CV --start-date 2024-04-09
now returns only relevant diffusion model papers published after April
2024.
* fix(skills): add query phrasing guide and enforce subagent delegation
Two fixes from Test 2 observations with DeepSeek:
1. Query phrasing: add a table showing good vs bad query examples.
The script wraps multi-word queries in double quotes for phrase
matching, so long queries like "diffusion models in computer vision"
return 0 results. Guide the LLM to use 2-3 core keywords + --category
instead.
2. Subagent enforcement: DeepSeek was extracting metadata inline via
python -c scripts instead of using the task tool. Strengthen Phase 3
to explicitly name the task tool, say "do not extract metadata
yourself", and explain why (token budget, isolation). This is more
direct than the previous natural-language-only approach while still
providing the reasoning behind the constraint.
* fix(skills): strengthen search keyword guidance and subagent enforcement
Address two issues found during end-to-end testing with DeepSeek:
1. Search retry: LLM passed full topic descriptions as queries (e.g.
"diffusion models in computer vision"), which returned 0 results due
to exact phrase matching and triggered retries. Added explicit
instruction to extract 2-3 core keywords before searching.
2. Subagent bypass: LLM used python -c to extract metadata instead of
dispatching via task tool. Added explicit prohibition list (python -c,
bash scripts, inline extraction) with ❌ markers for clarity.
* fix(skills): address Copilot review feedback on SLR skill
- Fix legacy arXiv ID parsing: preserve archive prefix for pre-2007
papers (e.g. hep-th/9901001 instead of just 9901001)
- Fix phase count: "four phases" -> "five phases"
- Add subagent_enabled prerequisite note to SKILL.md Notes section
- Remove PR-specific references ("PR 1") from ieee.md and bibtex.md
templates, replace with workflow-scoped wording
- Fix script header: "stdlib only" -> "no additional dependencies
required", fix relative path to github_api.py reference
- Remove reference to non-existent docs/enhancement/ path in header
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Add three new public skills to enhance DeerFlow's content creation capabilities:
- **academic-paper-review**: Structured peer-review-quality analysis of
research papers following top-venue review standards (NeurIPS, ICML, ACL).
Covers methodology assessment, contribution evaluation, literature
positioning, and constructive feedback with a 3-phase workflow.
- **code-documentation**: Professional documentation generation for software
projects, including README generation, API reference docs, architecture
documentation with Mermaid diagrams, and inline code documentation
supporting Python, TypeScript, Go, Rust, and Java conventions.
- **newsletter-generation**: Curated newsletter creation with research
workflow, supporting daily digest, weekly roundup, deep-dive, and industry
briefing formats. Includes audience-specific tone adaptation and
multi-source content curation.
All skills:
- Follow the existing SKILL.md frontmatter convention (name + description)
- Pass the official _validate_skill_frontmatter() validation
- Use hyphen-case naming consistent with existing skills
- Contain only allowed frontmatter properties
- Include comprehensive examples, quality checklists, and output templates
* feat: Add github PAT configs, allowing larger github API rates.
* Update comment to English for better clarity
* fix: Remove unused config lines in config.example.yaml and unreferenced declarations in app_config. Fix lint issues and update documentation.
* fix: Remove unused imports, and passed the ruff check.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* fix: add error handling for podcast generation failures
When TTS processing fails, the system was generating 0-second audio files
without any error indication. This fix adds:
1. Track failed TTS lines and log warning with indices
2. Raise ValueError when all TTS generation fails with helpful message
3. Check for empty audio output in mix_audio and raise error
4. Log success/failure ratio for debugging
Fixes#30
* fix: address Copilot review feedback
- Use `not audio` to catch both None and empty bytes
- Log failed lines with 1-based indices for user-friendly output
- Handle empty script case with clear error message
- Validate env vars before ThreadPoolExecutor for fast-fail on config errors
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: add citation/reference support to deep research reports (#1141)
- Enhance lead agent system prompt with mandatory citation requirements
after web_search/web_fetch tool usage
- Add citation examples and best practices to GitHub Deep Research skill
- Add citation hints to report template (Executive Summary, Key Analysis)
- Style regular markdown links in frontend for visual distinction
(color, underline, hover effect)
- Fix TitleMiddleware being registered when title generation is disabled
* fix: address PR review comments
- Revert TitleMiddleware conditional registration (agent.py) to avoid
sync/async incompatibility with DeerFlowClient
- Fix markdown link rendering: merge classNames instead of overwriting,
only set target=_blank for external http(s) URLs
- Remove unrelated package.json/pnpm-lock.yaml changes
* fix: use plain markdown links in Sources section for cleaner rendering
Inline citations in report body use [citation:Title](URL) for pill/badge style.
Sources section uses plain [Title](URL) for simple underlined link style.
* fix(frontend): render plain links as underlined text in artifact markdown
Only links with citation: prefix render as Badge pills.
Regular links in Sources section now render as underlined text links.
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
* feat: add claude-to-deerflow skill for DeerFlow API integration
Add a new skill that enables Claude Code to interact with the DeerFlow
AI agent platform via its HTTP API, including chat streaming and status
checking capabilities.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: fix telegram channel
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add IM channels system for Feishu, Slack, and Telegram integration
Bridge external messaging platforms to DeerFlow via LangGraph Server with
async message bus, thread management, and per-channel configuration.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: address review comments on IM channels system
Fix topic_id handling in store remove/list_entries and manager commands,
correct Telegram reply threading, remove unused imports/variables, update
docstrings and docs to match implementation, and prevent config mutation.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* update skill creator
* fix im reply text
* fix comments
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add agent management functionality with creation, editing, and deletion
* feat: enhance agent creation and chat experience
- Added AgentWelcome component to display agent description on new thread creation.
- Improved agent name validation with availability check during agent creation.
- Updated NewAgentPage to handle agent creation flow more effectively, including enhanced error handling and user feedback.
- Refactored chat components to streamline message handling and improve user experience.
- Introduced new bootstrap skill for personalized onboarding conversations, including detailed conversation phases and a structured SOUL.md template.
- Updated localization files to reflect new features and error messages.
- General code cleanup and optimizations across various components and hooks.
* Refactor workspace layout and agent management components
- Updated WorkspaceLayout to use useLayoutEffect for sidebar state initialization.
- Removed unused AgentFormDialog and related edit functionality from AgentCard.
- Introduced ArtifactTrigger component to manage artifact visibility.
- Enhanced ChatBox to handle artifact selection and display.
- Improved message list rendering logic to avoid loading states.
- Updated localization files to remove deprecated keys and add new translations.
- Refined hooks for local settings and thread management to improve performance and clarity.
- Added temporal awareness guidelines to deep research skill documentation.
* feat: refactor chat components and introduce thread management hooks
* feat: improve artifact file detail preview logic and clean up console logs
* feat: refactor lead agent creation logic and improve logging details
* feat: validate agent name format and enhance error handling in agent setup
* feat: simplify thread search query by removing unnecessary metadata
* feat: update query key in useDeleteThread and useRenameThread for consistency
* feat: add isMock parameter to thread and artifact handling for improved testing
* fix: reorder import of setup_agent for consistency in builtins module
* feat: append mock parameter to thread links in CaseStudySection for testing purposes
* fix: update load_agent_soul calls to use cfg.name for improved clarity
* fix: update date format in apply_prompt_template for consistency
* feat: integrate isMock parameter into artifact content loading for enhanced testing
* docs: add license section to SKILL.md for clarity and attribution
* feat(agent): enhance model resolution and agent configuration handling
* chore: remove unused import of _resolve_model_name from agents
* feat(agent): remove unused field
* fix(agent): set default value for requested_model_name in _resolve_model_name function
* feat(agent): update get_available_tools call to handle optional agent_config and improve middleware function signature
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Unifies market analysis, data analysis, and consulting reporting into a comprehensive consulting-analysis skill, enabling a two-phase workflow from analysis framework design to professional report generation. Introduces a DuckDB-based data analysis utility for Excel/CSV files and a chart-visualization skill with a flexible JS interface and extensive chart type documentation. Removes the legacy market analysis skill to streamline report generation and improve extensibility for consulting and data-driven workflows.
Explicitly prohibit parallel image generation to ensure each slide
can use the previous slide as a reference image for visual consistency.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Add "present_files" to disallowed_tools for bash and general-purpose
subagents to prevent them from presenting files directly. Also add the
new market-analysis skill for generating consulting-grade reports.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add accurate token counting using tiktoken library and significantly enhance
memory update prompts with detailed section guidelines, multilingual support,
and improved fact extraction. Update deep-research skill to be more proactive
for research queries.
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
- Add model-aware vision tool loading based on supports_vision flag
- Move view_image_tool from config to builtin tools for dynamic inclusion
- Add timeout to image search to prevent hanging requests
- Optimize image search results format using thumbnails
- Add image validation for reference images in generation
- Improve error handling with detailed messages
Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
Update presentation generation with contemporary design styles
(glassmorphism, dark-premium, neo-brutalist, etc.) and add a new
deep-research skill to guide thorough web research before content
generation tasks.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Creates presentations by generating AI images for each slide and composing
them into PPTX files. Features include:
- Multiple presentation styles (business, academic, minimal, keynote, creative)
- Visual consistency through reference image chaining (each slide uses the
previous slide as reference)
- Speaker notes from presentation plan
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Use ThreadPoolExecutor to generate audio for multiple script lines
concurrently, significantly speeding up podcast generation.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Remove LLM script generation from Python script, model now generates
JSON script directly (similar to image-generation skill)
- Add --transcript-file option to generate markdown transcript
- Add optional "title" field in JSON for transcript heading
- Remove dependency on OPENAI_API_KEY for podcast generation
- Update SKILL.md with new workflow and JSON format documentation
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add podcast-generation skill for creating tech explainer podcasts
- Include generate.py script with TTS synthesis capabilities
- Add tech-explainer template for structured podcast content
- Increase sandbox command timeout from 30s to 600s to support
longer-running skill scripts
- Add environment field to sandbox config for injecting env vars into container
- Support $VAR syntax to resolve values from host environment variables
- Refactor frontend API modules to use centralized getBackendBaseURL()
- Improve Doraemon skill with explicit input/output path arguments
- Add .env.example file
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add type, url, and headers fields to MCP server config
- Update MCP client to handle stdio, sse, and http transports
- Add todos field to ThreadState
- Add Deerflow branding requirement to frontend-design skill
- Update extensions_config.example.json with SSE/HTTP examples
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Implement a skills framework that enables specialized workflows for
specific tasks (e.g., PDF processing, web page generation). Skills are
discovered from the skills/ directory and automatically mounted in
sandboxes with path mapping support.
- Add SkillsConfig for configuring skills path and container mount point
- Implement dynamic skill loading from SKILL.md files with YAML frontmatter
- Add path mapping in LocalSandbox to translate container paths to local paths
- Mount skills directory in AIO Docker sandbox containers
- Update lead agent prompt to dynamically inject available skills
- Add setup documentation and expand config.example.yaml
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
