reverseclabs/spikee/target-implementation

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Guide for implementing Spikee target modules

Install

npx vskill@latest install reverseclabs/spikee/target-implementation

SKILL.md

Spikee Target Implementation Skill

This skill guides users through implementing a Spikee target module.

Domain

Creating Spikee target modules for testing LLMs, LLM applications, and guardrails.

Capabilities

This skill guides users through implementing a Spikee Target module by:

  1. Determining target type (LLM vs Guardrail vs Multi-turn)
  2. Selecting appropriate base class (Target, SimpleMultiTarget, or MultiTarget)
  3. Implementing required methods (get_description, get_available_option_values, process_input)
  4. Configuring authentication patterns (API keys, OAuth2, Managed Identity, GCP ADC, etc.)
  5. Handling guardrail triggers and response parsing
  6. Configuring proxy and TLS options

User Interaction

The skill helps users:

  1. Gather target system information (HTTP request/response samples, authentication details)
  2. Answer a decision tree to select the correct base class
  3. Match their authentication/transport pattern to Spikee templates
  4. Implement the target with all required error handling

Common Use Cases

  • Creating targets for custom LLM APIs (OpenAI-compatible and native SDKs)
  • Implementing multi-turn chatbot targets with session management
  • Building guardrail targets that return bool (True=bypassed, False=blocked)
  • Adding authentication handlers (API keys, bearer tokens, OAuth2, Azure IMDS, GCP ADC)

Dependencies

  • Requires Spikee installed with target templates
  • Follows spikee.templates module conventions

Available Base Classes

ScenarioBase ClassImport
Single-turn LLM or guardrailTargetfrom spikee.templates.target import Target
Multi-turn, spikee-managed historySimpleMultiTargetfrom spikee.templates.simple_multi_target import SimpleMultiTarget
Multi-turn, custom stateMultiTargetfrom spikee.templates.multi_target import MultiTarget

Authentication Patterns Supported

  1. Static API Key / Bearer Token
  2. Static Session Cookie
  3. Username / Password (Form Login)
  4. Azure Managed Identity (IMDS)
  5. GCP Application Default Credentials
  6. Auth0 / OAuth2 Refresh Token
  7. Internal JWT (Self-Fetched)

Response Handling

  • LLM targets: Return string (LLM reply), raise GuardrailTrigger for blocks
  • Guardrail targets: Return bool (True=bypassed, False=blocked)

Output Format

Generated file: {application}_{feature}.py in workspace/targets/

Related Resources

  • .github/skills/target-implementation/target-instructions.md (source documentation)
  • spikee/templates/target.py (base class template)
  • spikee/templates/simple_multi_target.py (multi-turn template)
  • spikee/templates/multi_target.py (complex multi-turn template)

Security

  • Security scanPassed, 95 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

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Source

Popularity

Repository stars
230
Repository forks
43
7-day trend score
27

Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.

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