sequence-alignment

by aipoch-ai

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SKILL.md About

---
name: sequence-alignment
description: A skill for performing sequence alignment using NCBI BLAST API. Supports nucleotide and protein sequence comparison against major biological databases.
license: MIT
skill-author: AIPOCH
---
# Sequence Alignment

A skill for performing sequence alignment using NCBI BLAST API. Supports nucleotide and protein sequence comparison against major biological databases.

## When to Use

- Use this skill when the task needs performing sequence alignment using NCBI BLAST API. Supports nucleotide and protein sequence comparison against major biological databases.
- Use this skill for data analysis tasks that require explicit assumptions, bounded scope, and a reproducible output format.
- Use this skill when the response must stay inside the documented task boundary instead of expanding into adjacent work.

## Key Features

See `## Features` above for related details.

- Scope-focused workflow aligned to: A skill for performing sequence alignment using NCBI BLAST API. Supports nucleotide and protein sequence comparison against major biological databases.
- Packaged executable path(s): `scripts/main.py`.
- Reference material available in `references/` for task-specific guidance.
- Structured execution path designed to keep outputs consistent and reviewable.

## Dependencies

See `## Prerequisites` above for related details.

- `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.

```bash
cd "20260318/scientific-skills/Data Analytics/sequence-alignment"
python -m py_compile scripts/main.py
python scripts/main.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/main.py` with the validated inputs.
4. Review the generated output and return the final artifact with any assumptions called out.

## Implementation Details

See `## Workflow` above for related 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/main.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.

## Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

```bash
python -m py_compile scripts/main.py
```

## Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

```bash
python -m py_compile scripts/main.py
python scripts/main.py --help
```

## Workflow

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.
2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.
3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.
4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.
5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

## Features

- **BLAST API Integration**: Query NCBI BLAST service for sequence similarity search
- **Multiple BLAST Programs**: blastn, blastp, blastx, tblastn, tblastx
- **Alignment Visualization**: Display results in human-readable format
- **Database Support**: nr, nt, swissprot, refseq, pdb, and more

## Usage

```text
python scripts/main.py --sequence "ATGCGTACGTAGCTAGCTAG" --program blastn --database nt --output results.txt
```

### Parameters

| Parameter | Description | Required |
|-----------|-------------|----------|
| `--sequence` | Query sequence (DNA/Protein) | Yes |
| `--program` | BLAST program: blastn, blastp, blastx, tblastn, tblastx | Yes |
| `--database` | Target database: nr, nt, swissprot, pdb, refseq_protein | Yes |
| `--output` | Output file path | No |
| `--format` | Output format: text, json, csv | No (default: text) |
| `--max_hits` | Maximum number of hits to return | No (default: 10) |
| `--evalue` | E-value threshold | No (default: 10) |

## Technical Difficulty

**Medium** - Requires understanding of BLAST algorithm, API handling with retry logic, and biological sequence formats.

## BLAST Programs Reference

| Program | Query Type | Database Type | Use Case |
|---------|-----------|---------------|----------|
| blastn | Nucleotide | Nucleotide | DNA vs DNA |
| blastp | Protein | Protein | Protein vs Protein |
| blastx | Nucleotide (translated) | Protein | DNA vs Protein |
| tblastn | Protein | Nucleotide (translated) | Protein vs DNA |
| tblastx | Nucleotide (translated) | Nucleotide (translated) | Translated DNA vs DNA |

## Example Workflows

### DNA Sequence Similarity Search
```text
python scripts/main.py --sequence "ATGGCCCTGTGGATGCGCTTCTTAGTCG" --program blastn --database nt --max_hits 5
```

### Protein Sequence Alignment
```text
python scripts/main.py --sequence "MKTAYIAKQRQISFVKSHFSRQLEERLGLIEVQAPILSRVGDGT" --program blastp --database swissprot --evalue 0.001
```

## Output Format

Results include:
- Query sequence info
- Hit definitions and accession numbers
- Alignment scores (bit score, e-value)
- Percent identity and similarity
- Alignment visualization with match/mismatch highlighting

## References

- [BLAST Documentation](references/blast_docs.md)
- [NCBI BLAST API Guide](references/ncbi_api_guide.md)

## Risk Assessment

| Risk Indicator | Assessment | Level |
|----------------|------------|-------|
| Code Execution | Python scripts with tools | High |
| Network Access | External API calls | High |
| File System Access | Read/write data | Medium |
| Instruction Tampering | Standard prompt guidelines | Low |
| Data Exposure | Data handled securely | Medium |

## Security Checklist

- [ ] No hardcoded credentials or API keys
- [ ] No unauthorized file system access (../)
- [ ] Output does not expose sensitive information
- [ ] Prompt injection protections in place
- [ ] API requests use HTTPS only
- [ ] Input validated against allowed patterns
- [ ] API timeout and retry mechanisms implemented
- [ ] Output directory restricted to workspace
- [ ] Script execution in sandboxed environment
- [ ] Error messages sanitized (no internal paths exposed)
- [ ] Dependencies audited
- [ ] No exposure of internal service architecture

## Prerequisites

No additional Python packages required.

## Evaluation Criteria

### Success Metrics
- [ ] Successfully executes main functionality
- [ ] Output meets quality standards
- [ ] Handles edge cases gracefully
- [ ] Performance is acceptable

### Test Cases
1. **Basic Functionality**: Standard input → Expected output
2. **Edge Case**: Invalid input → Graceful error handling
3. **Performance**: Large dataset → Acceptable processing time

## Lifecycle Status

- **Current Stage**: Draft
- **Next Review Date**: 2026-03-06
- **Known Issues**: None
- **Planned Improvements**: 
  - Performance optimization
  - Additional feature support

## Output Requirements

Every final response should make these items explicit when they are relevant:

- Objective or requested deliverable
- Inputs used and assumptions introduced
- Workflow or decision path
- Core result, recommendation, or artifact
- Constraints, risks, caveats, or validation needs
- Unresolved items and next-step checks

## Error Handling

- If required inputs are missing, state exactly which fields are missing and request only the minimum additional information.
- If the task goes outside the documented scope, stop instead of guessing or silently widening the assignment.
- If `scripts/main.py` fails, report the failure point, summarize what still can be completed safely, and provide a manual fallback.
- Do not fabricate files, citations, data, search results, or execution outcomes.

## Input Validation

This skill accepts requests that match the documented purpose of `sequence-alignment` and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

> `sequence-alignment` only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

## Response Template

Use the following fixed structure for non-trivial requests:

1. Objective
2. Inputs Received
3. Assumptions
4. Workflow
5. Deliverable
6. Risks and Limits
7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.

_meta.json Metadata

{
  "ownerId": "kn76fcc8jhxekae91m2ekbrsgn821avs",
  "publishedAt": 1775009554442,
  "slug": "sequence-alignment",
  "version": "1.0.0"
}