990d22009c6c9d2aa32d9be5e983114e1167c158
8
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 Evan
|
102b506b0b |
fix(agents,hands): per-agent/per-hand mcp_servers / skills allowlists (#87) (#92)
All 32 agent manifests and 17 hands shipped with empty mcp_servers /
skills lists, which the kernel interprets as "no filter" — every
globally-configured MCP server's tools and every installed skill get
injected into the prompt on every LLM call. On a typical instance (9
MCP servers, ~85 MCP tools + ~82 built-in tools) that's ~50k input
tokens per turn spent on definitions the agent never uses.
Changes
-------
32 agents/*/agent.toml:
- mcp_servers: 1-4 per agent. memory wherever state persists across
turns; fetch / exa-search / brave-search only where the prompt
actually calls for web; git / github / filesystem on engineering
agents; gmail / google-calendar / linear / jira on productivity
agents whose prompts mention them.
- skills: per-role allowlist driven by what the system_prompt names
(e.g. coder → rust/python/typescript/git/shell-scripting; devops-
lead → docker/kubernetes/terraform/ansible/ci-cd/helm/prometheus/
sysadmin). Generalists (assistant) keep skills = [] (see "Open
items" below).
- skills_disabled = true on the four short-conversational agents
(hello-world, recipe-assistant, health-tracker, home-automation).
Their system prompts never instruct the LLM to consult any skill,
so loading all 60 was pure waste. They also drop the explicit
max_history_messages override and inherit the kernel default (60).
- max_history_messages tiered by workload shape:
60 short conversational (hello-world, recipe, health-tracker,
home-automation) — inherits the rising kernel default
(`DEFAULT_MAX_HISTORY_MESSAGES = 60`); no override needed.
60 single-turn task agents (writer, translator, doc-writer,
email-assistant, customer-support, sales-assistant, recruit-
er, social-media, personal-finance, tutor, travel-planner,
meeting-assistant, ops, devops-lead, planner) — explicit
override at the same value to lock the cap if the kernel
default moves again.
80 multi-step / tool-heavy (coder, debugger, architect, code-
reviewer, test-engineer, security-auditor, analyst, data-
scientist, academic-researcher, researcher, legal-assistant)
120 coordinators (assistant, orchestrator) — long multi-agent
sessions where prompt-cache continuity is critical
All values sit at or above the kernel default. Pinning lower
would thrash the prompt cache (the failure mode #91 fixed for
the creator hand by *raising* the cap, not lowering it).
17 hands/*/HAND.toml:
- hand-level mcp_servers / skills now declared on every hand, so
every [agents.*] inside inherits a sensible allowlist.
- skills_disabled = true placed on each [agents.*] inside clip and
creator (pure media pipelines that don't benefit from any skill).
HandDefinitionRaw in librefang-hands does NOT have a top-level
skills_disabled field — declaring it at the hand top level would
be silently dropped by serde, so the setting must live on the
AgentManifest of each sub-agent role.
- devteam: expand existing mcp_servers = ["github"] to include
memory / git / filesystem; populate skills with the expected
dev-team expertise (replacing the placeholder skills = []).
- wiki: replace placeholder mcp_servers = [] with [memory, fetch,
filesystem]. Hand-level skills stays [].
- lead: hand-level skills was originally [email-writer, writing-
coach, interview-prep]; interview-prep is for job-interview
preparation, not lead generation. Replaced with data-analyst
(used by the qualification-scoring step in the prompt).
schema.toml: register mcp_servers / skills / max_history_messages on
the agent field schema so machine consumers (RegistrySchema in
librefang-types) see the new top-level fields. The
max_history_messages description now points at
librefang_runtime::agent_loop::DEFAULT_MAX_HISTORY_MESSAGES (60
today) by name, so the schema doesn't go stale when the constant
moves again.
agents/README.md: example block + "Adding a New Agent" checklist
mention the allowlists; max_history_messages example is shown
commented out with a prompt-cache caveat.
Open items
----------
`assistant` (the default user-facing agent) keeps `skills = []`
deliberately. It is the generalist entry point — capping its skill
surface at a small allowlist would defeat its "delegate to any
specialist" job. The trade-off is that this single agent still pays
the full skill-definition load on every turn; operators who want a
strict allowlist for `assistant` can override it after install.
Why not adopt PR #89's approach
-------------------------------
#89 covers similar ground but with three issues this PR avoids:
1. mcp_servers = ["_none"] sentinel. #89's body explicitly notes
it's pending upstream librefang#4808 (mcp_disabled). Shipping a
magic-string today means coming back later to clean it up. This
PR uses real allowlists.
2. max_history_messages = 8 / 12 / 15 / 20. Far below today's
kernel default (60) and #91's direction for long-workflow hands
(80–120). Every turn that hits the cap invalidates the cached
prompt prefix; the cost of cache misses exceeds the saving from
shorter history. This PR uses 60–120.
3. Doubling max_llm_tokens_per_hour (coder 200k→500k, assistant
300k→500k) widens the per-agent budget — the opposite direction
from #87's "reduce per-call cost" goal. Left to the operator's
instance-specific tuning.
Refs librefang/librefang-registry#87, librefang/librefang-registry#89
|
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|
Evan
|
d4f15fd662 |
feat: add web_search capability to all agents and hands (#74)
Adds the web_search tool to every agent.toml and hand HAND.toml that did not already declare it. Without this capability the runtime gates the tool with 'Capability denied: tool not in allowed list', leaving agents unable to perform web searches even when a search provider is configured. For tools arrays that already contained web_fetch, web_search is inserted directly after it (its natural companion). For arrays without web_fetch, web_search is appended to the end. 24 files updated total: 21 agents and 3 hands. |
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|
Evan
|
28ea31b073 |
chore(agents): drop GEMINI_API_KEY fallback from generic templates (#68)
These 11 templates are the general-purpose ones that don't depend on any particular model at the primary level (`[model] provider = "default"`). They also ship a secondary `[[fallback_models]]` block pointing at `gemini-2.0-flash` with `api_key_env = "GEMINI_API_KEY"`. That default hurts everyone who doesn't happen to have `$GEMINI_API_KEY` set — every agent boot logs `WARN Fallback driver 'gemini' failed to init: Missing API key`, once per turn per agent. The templates that actually intend to use Gemini as their primary model (analyst, coder, researcher, code-reviewer, debugger, legal-assistant, data-scientist, academic-researcher, test-engineer) are left untouched — those declare Gemini in `[model]`, which is an intentional design choice, not a hidden fallback. Users who want a Gemini fallback chain for generic agents can add `[[fallback_models]]` themselves in `~/.librefang/workspaces/agents/...` once they've set `$GEMINI_API_KEY`. Removed from: assistant, customer-support, devops-lead, doc-writer, email-assistant, meeting-assistant, planner, recruiter, sales-assistant, social-media, writer |
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|
Evan
|
7881d327a5 |
refactor: migrate icon fields from emoji to lucide:<name> tokens (#63)
* refactor: migrate icon fields from emoji to lucide:<name> tokens
Every TOML manifest's `icon = "<emoji>"` line is replaced with
`icon = "lucide:<kebab-name>"` — a reference to a lucide-react icon,
which the librefang.ai site and dashboard render as crisp SVG. Reasons
for the switch:
- Emoji render very differently across OS/browser/font stacks; the
registry catalog looked inconsistent from one row to the next.
- Five manifests (clip / creator / linkedin / reddit / twitter) had
their icons stored as literal Python-style escape strings
("\\U0001F3AC") because the TOML parser upstream never decoded
them. Switching away from emoji drops that class of bug entirely.
- As a drive-by, also decode the \\uXXXX accent escapes in the
[i18n.fr] block of hands/creator/HAND.toml so "Créateur" shows
up correctly.
87 files touched. example manifests left untouched (still "TODO").
* fix: backfill i18n name + drop the single-member email category
- Every existing [i18n.<lang>] block now has a `name` field. 60 files
previously translated description but kept the English name
implicitly — which rendered as "some English some Chinese" in the
registry UI. Fill in the missing name from the English brand (or a
known localized equivalent: DingTalk→钉钉, Feishu→飞书, Email→
电子邮件 / メール / E-Mail / Correo / Courriel, and a handful of
hands that have Chinese product names like 视频剪辑 Hand).
- channels/email.toml was the only item under category="email";
reclassify it as "messaging" so the sub-category filter chip list
on the category page isn't littered with singletons.
* feat(i18n): localize 76 agents/integrations/plugins into 7 languages
Adds full [i18n.zh], [i18n.zh-TW], [i18n.ja], [i18n.ko], [i18n.de],
[i18n.es], [i18n.fr] blocks with name + description to every manifest
that previously shipped English-only.
Coverage:
- 32 agents (academic-researcher, analyst, architect, assistant,
code-reviewer, coder, customer-support, data-scientist, debugger,
devops-lead, doc-writer, email-assistant, health-tracker,
hello-world, home-automation, legal-assistant, meeting-assistant,
ops, orchestrator, personal-finance, planner, recipe-assistant,
recruiter, researcher, sales-assistant, security-auditor,
social-media, test-engineer, translator, travel-planner, tutor,
writer)
- 33 integrations (AWS, Azure, Bitbucket, Brave Search, Discord,
Dropbox, Elasticsearch, Exa Search, Fetch, Filesystem, GCP, Git,
GitHub, GitLab, Gmail, Google Calendar, Google Drive, Google Maps,
Jira, Linear, Memory, MongoDB, Notion, PostgreSQL, Puppeteer, Redis,
Sentry, Sequential Thinking, Slack, SQLite, Teams, Time, Todoist) —
brand names kept as-is across all locales, only descriptions
translated.
- 11 plugins (auto-summarizer, context-decay, conversation-logger,
episodic-memory, guardrails, keyword-memory, mempalace-indexer,
sentiment-tracker, todo-tracker, topic-memory, user-profile)
The descriptions are one-line summaries — hand-translated rather than
machine-generated, so technical terms (MCP, PR, CI/CD, etc.) stay
consistent across locales.
* feat(i18n): close remaining per-lang gaps for channels, workflows, devteam
Third pass on i18n coverage. Every non-example manifest now carries a
full set of [i18n.zh], [i18n.zh-TW], [i18n.ja], [i18n.ko], [i18n.de],
[i18n.es], [i18n.fr] blocks.
- 44 channel adapters: added French descriptions (zh/zh-TW/ja/ko/de/es
were already present). Brand names kept as-is in all locales so users
recognize Discord / Slack / LINE / etc. consistently.
- 22 workflows: filled zh-TW / ja / ko / de / es / fr blocks. Each
translation mirrors the existing zh one in structure and tone so the
catalog reads consistently across locales.
- hands/devteam/HAND.toml: added the four langs that were missing
(zh-TW, de, es, fr).
Only the 6 templates under examples/ are left without i18n blocks on
purpose — they still contain "TODO:" placeholders.
|
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|
Evan
|
d778da72a2 |
fix(validate): check for [agents] instead of [agent] in HAND.toml (#15)
* fix(validate): check for [agents] instead of [agent] in HAND.toml All 14 hands use [agents.main] (plural) for multi-agent config, but the validator was checking for [agent] (singular), causing all hands to fail validation. * fix(routing): resolve 19 routing alias collisions Agent is a sub-unit of hand, so hands take priority for routing. Remove conflicting aliases from agent side when hand already owns them. - analyst: remove data analysis, analyze data, dashboard (owned by hand/analytics) - data-scientist: remove statistical analysis, forecast, prediction (owned by hand/analytics, hand/predictor) - sales-assistant: remove prospecting, sales, pipeline (owned by hand/lead, hand/devops) - devops-lead: remove incident response, kubernetes, terraform (owned by hand/devops) - researcher: remove deep research, research, literature review (owned by hand/researcher) - academic-researcher: remove literature review, systematic review (owned by hand/researcher) - social-media: remove duplicate content calendar from weak_aliases - hand/collector: remove competitive analysis (owned by hand/strategist) |
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|
EvanandClaude Opus 4.6
|
8f2244eb6f |
chore: remove router agent (#5)
* chore: remove router agent builtin:router has been replaced by LLM intent routing in the kernel. Assistant is now the sole entry point — see librefang/librefang#1336. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> * style: format all TOML files with taplo Fix CI taplo format check by running `taplo fmt` on all 132 TOML files. --------- Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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Evan Hu
|
4b38372463 |
docs: add README for every subdirectory
33 agent READMEs, 14 hand READMEs, 2 plugin READMEs (echo-memory + hooks), and 2 skill READMEs (custom-skill-prompt + custom-skill-python). Each README documents the component's purpose, configuration, and usage based on its TOML definition. |
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Evan Hu
|
17d32ed4a7 |
feat: sync content definitions from core repo
Copy all TOML content definitions from librefang core repo: - 33 agent definitions (agents/*/agent.toml) - 14 hand definitions with docs (hands/*/HAND.toml + SKILL.md) - 25 integration templates (integrations/*.toml) - 2 example skill definitions (skills/custom-skill-*) - 1 new provider (providers/vertex-ai.toml) Part of the framework-vs-content registry split (RFC v0.7). |