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skills support

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Luxferre
2026-09-10 10:38:36 +03:00
parent 5b5853a2dd
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3 changed files with 220 additions and 2 deletions
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@@ -70,6 +70,7 @@ All implementations read `model.cfg` (or `.bantam.cfg`, which takes priority if
- `/cfg <param> [val]` — inspect or update a configuration parameter live (writes to `.bantam.cfg`)
- `/model [val]` — alias for `/cfg model` (inspect or set the model)
- `/endpoint [val]` — alias for `/cfg endpoint` (inspect or set the API endpoint)
- `/skill` — with no argument, list every skill under the configured skills directory (or report that none are configured); with `<name> [prompt]`, load `<skills_dir>/<name>/SKILL.md` (or an absolute path when no skills dir is set) and send its contents prefixed to the optional `prompt` as the next user turn
- `/models` — query the `/models` path on the current inference endpoint and print a plain list of supported model IDs, marking the currently configured model with a leading `* ` (Go port)
- `!<cmd>` — execute a shell command directly through `shell_exec` without adding the result to the conversation context (Go port)
- `/help` — show all supported commands
@@ -117,7 +118,7 @@ Using these rules, everyone can build their own copy of Bantam from scratch in l
2. Read model parameters from the config file (`.bantam.cfg` if present, else `model.cfg`) in `key=value` format and discover context window size.
3. Prepare a new message list with the system prompt (`role: "system"`).
4. Read the first command-line parameter. If non-empty, read user prompt from the specified file. If prefixed with `!`, execute the shell command directly via `shell_exec` and exit. Otherwise, append to `messages` (`role: "user"`), run `AL(cfg, messages)`, display token usage, and exit.
5. Read user prompt from standard input (with `readline` line editing and history in `~/.bantam_history`; **Ctrl+J** inserts a real newline into the line being edited). If equal to `/quit` or EOF, exit. If equal to `/clear`, reset `messages` to step 3 and return to step 5. If starting with `/save`, write the whole `messages` array to `~/.bantam/sessions/<name>.json` (or `<project-md5>.json` if no name is given) and return to step 5. If equal to `/continue` or `/cont`, load the session corresponding to the current project's MD5 hash and return to step 5. If equal to `/list`, print saved sessions and their summaries (marking current project session) and return to step 5. If starting with `/load`, replace `messages` with the saved session's messages (by exact id or unique prefix) and return to step 5. If equal to `/compact`, ask the LLM to summarize the conversation by appending the compaction prompt to derive the summary, replace `messages` with `[system, summary-user-message]`, and return to step 5. If starting with `/cfg`, display the current value (`/cfg <param>`) or update the config live by writing to `.bantam.cfg` (`/cfg <param> <val>`) and return to step 5. `/model` and `/endpoint` are aliases for `/cfg model` and `/cfg endpoint` respectively and behave the same way. If equal to `/models`, query the `/models` path on the current inference endpoint and print a plain list of supported model IDs (the currently configured model marked with a leading `* `), then return to step 5. If starting with `!`, execute the command directly via `shell_exec` without adding the result to `messages` and return to step 5. If equal to `/help`, print the command list and return to step 5. After every user turn and on exit, auto-save `messages` to `~/.bantam/sessions/<project-md5>.json`.
5. Read user prompt from standard input (with `readline` line editing and history in `~/.bantam_history`; **Ctrl+J** inserts a real newline into the line being edited). If equal to `/quit` or EOF, exit. If equal to `/clear`, reset `messages` to step 3 and return to step 5. If starting with `/save`, write the whole `messages` array to `~/.bantam/sessions/<name>.json` (or `<project-md5>.json` if no name is given) and return to step 5. If equal to `/continue` or `/cont`, load the session corresponding to the current project's MD5 hash and return to step 5. If equal to `/list`, print saved sessions and their summaries (marking current project session) and return to step 5. If starting with `/load`, replace `messages` with the saved session's messages (by exact id or unique prefix) and return to step 5. If equal to `/compact`, ask the LLM to summarize the conversation by appending the compaction prompt to derive the summary, replace `messages` with `[system, summary-user-message]`, and return to step 5. If starting with `/cfg`, display the current value (`/cfg <param>`) or update the config live by writing to `.bantam.cfg` (`/cfg <param> <val>`) and return to step 5. `/model` and `/endpoint` are aliases for `/cfg model` and `/cfg endpoint` respectively and behave the same way. If equal to `/skill` (no argument), list every skill under the configured skills directory (or report that none is configured) and return to step 5. If starting with `/skill`, resolve the skill (a `<skills_dir>/<name>/SKILL.md` file, or an absolute path to a skill directory or `SKILL.md` file when no skills directory is configured), prefix its contents to the optional remaining text, and send the result as the next user turn (returning to step 5 after the response). If equal to `/models`, query the `/models` path on the current inference endpoint and print a plain list of supported model IDs (the currently configured model marked with a leading `* `), then return to step 5. If starting with `!`, execute the command directly via `shell_exec` without adding the result to `messages` and return to step 5. If equal to `/help`, print the command list and return to step 5. After every user turn and on exit, auto-save `messages` to `~/.bantam/sessions/<project-md5>.json`.
6. Append user prompt to `messages` (`role: "user"`), run `AL(cfg, messages)`, display token usage, check 60% context threshold for auto-compaction, and go to step 5.
### Agentic loop (`AL(cfg, messages)`) function
@@ -156,6 +157,7 @@ If the API rejects the request with an `Invalid assistant message: content or to
- `reasoning_effort` (reasoning effort level, forwarded to chat completions API, default `high`)
- `bantam_tools_dir` (optional path to a directory of extra shell tools; the Go port appends `"Extra shell tools can be found at <dir>"` to the system prompt at startup when set. The `BANTAM_TOOLS_DIR` environment variable overrides this and is checked first; if neither is set, nothing is appended. Note: this is an agent-internal hint, not forwarded to the API.)
- `bantam_skills_dir` (optional path to a directory of reusable *skills*; each skill lives in its own subdirectory as `<skill_name>/SKILL.md`. When set, the Go port appends `"Skills may be discovered and invoked from <dir>"` to the system prompt at startup, and the `/skill <skill_name> [prompt]` command loads a skill's `SKILL.md` and runs it as a prompt. The `BANTAM_SKILLS_DIR` environment variable overrides this and is checked first; if neither is set, `/skill` accepts an absolute path to a skill directory or `SKILL.md` file instead. Note: this is an agent-internal hint, not forwarded to the API.)
The Go port also supports SOCKS5 proxying via the `SOCKS_PROXY` (or `socks_proxy`) environment variable (e.g. `SOCKS_PROXY=socks5://127.0.0.1:1080` or `SOCKS_PROXY=127.0.0.1:1080`), falling back to standard `HTTP_PROXY` / `HTTPS_PROXY` environment variables.
@@ -223,6 +225,17 @@ The `extras/` directory contains small, dependency-light shell scripts that exte
If you keep your own collection of helper scripts, point Bantam at them with the `BANTAM_TOOLS_DIR` environment variable or the `bantam_tools_dir` key in the config file (`.bantam.cfg` if present, else `model.cfg`). When either is defined (environment variable taking precedence over the config key), the Go port appends the line `Extra shell tools can be found at <dir>` to the system prompt at startup, so the agent is aware of where to look for them. The `extras/` scripts shipped here are just examples of what such a directory can contain.
## Skills
A *skill* is a reusable, self-contained instruction bundle the agent can load on demand. Each skill is a directory containing a `SKILL.md` file with the skill's prompt/instructions. Point Bantam at a skills directory with the `BANTAM_SKILLS_DIR` environment variable or the `bantam_skills_dir` key in the config file (`.bantam.cfg` if present, else `model.cfg`); the environment variable takes precedence. When either is set, the Go port appends `Skills may be discovered and invoked from <dir>` to the system prompt at startup, and the agent can run a skill with:
```text
/skill # list every skill under the configured skills directory
/skill <name> [prompt] # loads <skills_dir>/<name>/SKILL.md and runs it as a prompt
```
A bare `/skill` (no name) lists all skills found under the configured skills directory — a subdirectory is treated as a skill only if it contains a `SKILL.md` file — or reports that no skills directory is configured. The contents of `SKILL.md` are prefixed to the optional `prompt` and sent as the next user turn. If neither `BANTAM_SKILLS_DIR` nor `bantam_skills_dir` is set, `/skill <name>` accepts an absolute path instead: either a skill directory (e.g. `/abs/path/to/skill`, which resolves to `/abs/path/to/skill/SKILL.md`) or a direct path to a `SKILL.md` file.
### `extras/websearch`
@@ -309,6 +322,10 @@ The default system prompt instructs the agent to respect `AGENTS.md` contents in
Set the `BANTAM_TOOLS_DIR` environment variable (or the `bantam_tools_dir` key in the config file — `.bantam.cfg` if present, else `model.cfg`) to a directory containing your helper scripts. When defined, the Go port appends `Extra shell tools can be found at <dir>` to the system prompt at startup, making the agent aware of them. The environment variable takes precedence over the config key; if neither is set, nothing is appended.
### How do I give Bantam reusable skills?
Set the `BANTAM_SKILLS_DIR` environment variable (or the `bantam_skills_dir` key in the config file — `.bantam.cfg` if present, else `model.cfg`) to a directory where each subdirectory is a skill containing a `SKILL.md` file. When defined, the Go port appends `Skills may be discovered and invoked from <dir>` to the system prompt at startup, and you (or the agent) can run a skill with `/skill <name> [prompt]`. The environment variable takes precedence over the config key; if neither is set, `/skill` accepts an absolute path to a skill directory or `SKILL.md` file instead.
### Is there any common config place for Bantam?
No, loading the config file (`.bantam.cfg` if present, else `model.cfg`) is deliberately only supported from the current working directory. This allows natural separation of configs per project. In case there's no config file inside the project, Bantam will use the `openrouter/free` model from Kilo Code with the temperature 0.7.