Kegg API

Source: https://github.com/aipoch/medical-research-skills

KEGG API Skill

This skill allows querying the KEGG (Kyoto Encyclopedia of Genes and Genomes) database via its REST API.

When to Use

• Use this skill when the request matches its documented task boundary.
• Use it when the user can provide the required inputs and expects a structured deliverable.
• Prefer this skill for repeatable, checklist-driven execution rather than open-ended brainstorming.

Key Features

• Scope-focused workflow aligned to: Access the KEGG database API to retrieve biological data (genes, pathways, compounds, drugs). Invoke when the user asks to search, list, or get details from KEGG.
• Packaged executable path(s): scripts/kegg_client.py.
• Reference material available in references/ for task-specific guidance.
• Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

• Python: 3.10+. Repository baseline for current packaged skills.
• Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.

Example Usage

See ## Usage above for related details.

cd "20260316/scientific-skills/Evidence Insight/kegg-api"
python -m py_compile scripts/kegg_client.py
python scripts/kegg_client.py --help

Example run plan:

1. Confirm the user input, output path, and any required config values.
2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
3. Run python scripts/kegg_client.py with the validated inputs.
4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

• Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
• Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
• Primary implementation surface: scripts/kegg_client.py.
• Reference guidance: references/ contains supporting rules, prompts, or checklists.
• Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
• Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

Operations

1. info: Display database statistics.

   • Usage: info <database>
   • Example: info pathway

2. list: List entry identifiers.

   • Usage: list <database>
   • Example: list organism

3. find: Search for entries.

   • Usage: find <database> <query>
   • Example: find genes shiga+toxin

4. get: Retrieve entry details.

   • Usage: get <dbentries>
   • Example: get hsa:10458

5. conv: Convert identifiers.

   • Usage: conv <target_db> <source_db>
   • Example: conv eco ncbi-geneid

6. link: Find related entries.

   • Usage: link <target_db> <source_db>
   • Example: link pathway hsa

7. ddi: Drug-drug interactions.

   • Usage: ddi <dbentry>
   • Example: ddi D00564

Usage

Run the python script scripts/kegg_client.py.

python scripts/kegg_client.py <operation> <args...> [--option <opt>]

Examples

# Get info about pathways
python scripts/kegg_client.py info pathway

# Find genes related to "insulin" in humans (hsa)
python scripts/kegg_client.py find hsa insulin

# Get details for a specific gene
python scripts/kegg_client.py get hsa:3630

# Link genes to pathways
python scripts/kegg_client.py link pathway hsa:3630

When Not to Use

• Do not use this skill when the required source data, identifiers, files, or credentials are missing.
• Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
• Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.