docs(prompt): list load_skill in the model's toolbox reference (#434)
The new `load_skill` tool was registered into the agent and plan mode tool sets in 0c1699 but the prompt's `## Toolbox` quick-reference still listed only the legacy progressive- disclosure pattern (system prompt → read_file). The model has to read the tool description to know `load_skill` exists, but without a hint in the toolbox it's easy to miss when scanning. Adds a `**Skills**` line that points at `load_skill` and explains when to prefer it over `read_file` + `list_dir`. Pulls from the existing `## Skills` section above for context, so the model sees one short cross-reference instead of duplicate setup instructions. No code change; prompt-only doc edit. Existing prompt-stability tests pass unchanged because they don't compare prose.
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@@ -136,6 +136,7 @@ When context is deep (past a soft seam): cache reasoning conclusions in concise
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- **Git / diag / tests**: `git_status`, `git_diff`, `git_show`, `git_log`, `git_blame`, `diagnostics`, `run_tests`, `review`.
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- **Sub-agents**: `agent_spawn` (`spawn_agent`, `delegate_to_agent`), `agent_result`, `agent_cancel` (`close_agent`), `agent_list`, `agent_wait` (`wait`), `agent_send_input` (`send_input`), `agent_assign` (`assign_agent`), `resume_agent`.
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- **Recursive LM (long inputs / parallel reasoning)**: `rlm` — load a file/string as `context` in a Python REPL, sub-agent writes Python that calls `llm_query`/`llm_query_batched`/`rlm_query` to chunk, compare, critique, and synthesize; returns the synthesized answer. Read-only.
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- **Skills**: `load_skill` (#434) — when the user names a skill or the task matches one in the `## Skills` section above, call this with the skill id to pull its `SKILL.md` body and companion-file list into context in one tool call. Faster than `read_file` + `list_dir`.
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- **Other**: `code_execution` (Python sandbox), `validate_data` (JSON/TOML), `request_user_input`, `finance` (market quotes), `tool_search_tool_regex`, `tool_search_tool_bm25` (deferred tool discovery).
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Multiple `tool_calls` in one turn run in parallel. `web_search` returns `ref_id`s — cite as `(ref_id)`.
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