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Apply mechanical punctuation and wording-token fixes

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Alex Schapiro
2026-08-14 19:42:22 +00:00
parent 8ca0c4a9b8
commit 79630f9ba0
19 changed files with 101 additions and 101 deletions
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docs/advanced/configuration.mdx
+4 -4
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@@ -8,7 +8,7 @@ Configure Strix using environment variables or a config file.
## LLM Configuration
<ParamField path="STRIX_LLM" type="string" required>
Model name in LiteLLM format (e.g., `openai/gpt-5.4`, `anthropic/claude-sonnet-4-6`).
Model name in LiteLLM format (for example, `openai/gpt-5.4`, `anthropic/claude-sonnet-4-6`).
</ParamField>
<ParamField path="LLM_API_KEY" type="string">
@@ -20,7 +20,7 @@ Configure Strix using environment variables or a config file.
</ParamField>
<ParamField path="LLM_EXTRA_HEADERS" type="string">
Extra HTTP headers sent on every LLM request, as a JSON object (e.g.
Extra HTTP headers sent on every LLM request, as a JSON object (for example
`{"X-Feature-Key":"value","X-Tenant":"acme"}`). Useful for OpenAI-compatible
gateways that require attribution or routing headers in addition to the bearer
token. The bearer token itself still comes from `LLM_API_KEY`. Applies to both
@@ -65,8 +65,8 @@ affecting the agents that do the actual testing.
<ParamField path="DEDUPE_LLM_EXTRA_HEADERS" type="string">
Optional JSON object of extra HTTP headers sent on every deduplication-model
request, e.g. `{"X-Feature-Key":"value"}`. A dedicated dedupe model never
inherits `LLM_EXTRA_HEADERS`; set this when its endpoint needs custom headers.
request, for example `{"X-Feature-Key":"value"}`. A dedicated dedupe model never
inherits `LLM_EXTRA_HEADERS`. Set this when its endpoint needs custom headers.
</ParamField>
<ParamField path="STRIX_DEDUPE_REASONING_EFFORT" type="string">
docs/advanced/skills.mdx
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@@ -7,7 +7,7 @@ Skills are structured knowledge packages that give Strix agents deep expertise i
## The Idea
LLMs have broad but shallow security knowledge. They know _about_ SQL injection, but lack the nuanced techniques that experienced pentesters use—parser quirks, bypass methods, validation tricks, and chain attacks.
LLMs have broad but shallow security knowledge. They know _about_ SQL injection, but lack the nuanced techniques that experienced pentesters use: parser quirks, bypass methods, validation tricks, and chain attacks.
Skills inject this deep, specialized knowledge directly into the agent's context, transforming it from a generalist into a specialist for the task at hand.
@@ -25,9 +25,9 @@ create_agent(
The skills are injected into the agent's system prompt, giving it access to:
- **Advanced techniques** — Non-obvious methods beyond standard testing
- **Working payloads** — Practical examples with variations
- **Validation methods** — How to confirm findings and avoid false positives
- **Advanced techniques:** Non-obvious methods beyond standard testing
- **Working payloads:** Practical examples with variations
- **Validation methods:** How to confirm findings and avoid false positives
## Skill Categories
@@ -138,7 +138,7 @@ How to confirm findings and avoid false positives.
Community contributions are welcome. Create a `.md` file in the appropriate category with YAML frontmatter (`name` and `description` fields). Good skills include:
1. **Real-world techniques** — Methods that work in practice
2. **Practical payloads** — Working examples with variations
3. **Validation steps** — How to confirm without false positives
4. **Context awareness** — Version/environment-specific behavior
1. **Real-world techniques**: Methods that work in practice
2. **Practical payloads**: Working examples with variations
3. **Validation steps**: How to confirm without false positives
4. **Context awareness**: Version/environment-specific behavior