P2: move compactor -> compact/ + step instrumentation -> run/steps.go

- compact/compactor.go: the per-run stateful context compactor (token-threshold
  gate, fast-tier middle summarisation, fold memory) lifted from mort's
  skillexec/compactor.go. Self-contained; its only dependency is a ModelResolver
  func (model.ParseModelForContext satisfies it) + a token threshold.
- run/steps.go: the step-emission/instrumentation (stepEmitter, tool->kind/
  summary mapping with redaction, Result.Steps accumulation) from agentexec,
  repointed onto executus/tool.

Both build green. With the run-loop mechanics, RunnableAgent DTO, run.Ports,
compactor, and step instrumentation now all in place, the remaining P2 work is
the run.Executor itself (wiring these + majordomo's agent loop), which makes
executus runnable.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-06-26 20:36:32 -04:00
committed by steve
parent d9b44387f5
commit 130c2bdfab
3 changed files with 741 additions and 2 deletions
+3 -2
View File
@@ -45,7 +45,8 @@ CORE (majordomo + stdlib):
identity/ caller identity seams [P0 ✓] identity/ caller identity seams [P0 ✓]
run/ run-loop mechanics + RunnableAgent DTO + [P2 wip] run/ run-loop mechanics + RunnableAgent DTO + [P2 wip]
nil-safe run.Ports (Audit/Budget/Critic/ nil-safe run.Ports (Audit/Budget/Critic/
Checkpointer/PaletteSource) defined; the Checkpointer/PaletteSource) + step
instrumentation (steps.go) done; the
agentexec+skillexec -> run.Executor MERGE agentexec+skillexec -> run.Executor MERGE
(consuming Ports) is the remaining P2 work [P2] (consuming Ports) is the remaining P2 work [P2]
dispatchguard/ loop/depth/fan-out caps [P0 ✓] dispatchguard/ loop/depth/fan-out caps [P0 ✓]
@@ -55,7 +56,7 @@ CORE (majordomo + stdlib):
(convar->config.Source; UsageSink/TraceSink seams; GenerateWith[T] (convar->config.Source; UsageSink/TraceSink seams; GenerateWith[T]
structured output — no separate structured/ pkg) structured output — no separate structured/ pkg)
llmmeta/ shared meta-LLM helper over model/ [P1 ✓] llmmeta/ shared meta-LLM helper over model/ [P1 ✓]
compact/ context compactor (WithCompactor hook) [P2] compact/ context compactor (WithCompactor hook) [P2]
tools/{web,net,store,compose,meta,comms} generic tools [P3] tools/{web,net,store,compose,meta,comms} generic tools [P3]
BATTERIES (opt-in siblings, each nil-safe + a default): BATTERIES (opt-in siblings, each nil-safe + a default):
+331
View File
@@ -0,0 +1,331 @@
// V15.2 context compactor (re-based on majordomo).
//
// Why: the agent loop accumulates tool results indefinitely. A
// research-heavy run with many web_search / read_page / http_get
// results easily crosses 200K tokens and trips the model's HTTP-400
// "prompt too long" rejection mid-run (observed at 410K tokens on
// qwen3-coder:480b which has a 262K cap). majordomo's agent loop calls
// the compactor with the full message slice before every model call;
// the compactor returns a shorter slice that preserves the system
// prompt + recent messages, with the middle range replaced by a
// synthetic summary.
//
// Strategy (unchanged from the agentkit era):
// - Keep any leading system message verbatim. (Under majordomo the
// system prompt normally travels in Request.System, not in the
// message slice, so this is defensive.)
// - Keep the last KeepRecent messages verbatim. This ensures the
// agent has fresh tool state to act on; compacting too aggressively
// would strip the in-flight context it needs to make the next
// decision.
// - Compress the middle range via a single fast-tier LLM call that
// receives the middle messages as raw text and produces a paragraph
// summary (URLs visited, key findings, file_ids created, what the
// agent is trying to accomplish).
// - Replace the middle range with one synthetic user-role message
// containing the summary. (user-role chosen because tool-result-role
// would be ambiguous without a matching tool_call_id.)
//
// What moved in the majordomo conversion:
// - The token-threshold gate lives HERE now. agentkit estimated
// tokens and only invoked the compactor past a configured
// threshold; majordomo's hook fires before every model call, so
// the threshold check (estimateTokens vs the per-run threshold the
// executor computes from the model's context limit) is the
// compactor's first step.
// - The compactor is per-run STATEFUL: majordomo does not replace
// the loop's internal transcript with the compacted slice (the
// hook shapes only what is SENT), so without memory the middle
// would be re-summarised from scratch on every step past the
// threshold. The state remembers how far the transcript has been
// folded into the running summary and folds the previous summary
// into the next one instead of re-paying for it.
//
// Failure path: any error (LLM unavailable, malformed response, etc.)
// is returned to the agent loop, which treats compactor errors as
// non-fatal and sends the original slice — if the next model call hits
// the provider's limit, the existing HTTP-400 error path takes over.
package compact
import (
"context"
"errors"
"fmt"
"strings"
"sync"
"gitea.stevedudenhoeffer.com/steve/majordomo/llm"
)
// ModelResolver resolves a tier/spec to a usable llm.Model (and an enriched
// context for usage attribution). model.ParseModelForContext satisfies it.
type ModelResolver func(ctx context.Context, tier string) (context.Context, llm.Model, error)
// Compactor is the per-run compaction hook handed to the agent loop
// (matches the signature agent.WithCompactor expects).
type Compactor = func(ctx context.Context, msgs []llm.Message) ([]llm.Message, error)
// CompactionEvent describes one fired compaction so the executor can
// log it to skill_run_logs ("compaction_fired").
type CompactionEvent struct {
// MessagesBefore/After count the messages that would have been
// sent without/with this compaction.
MessagesBefore int
MessagesAfter int
// TokensBefore/After are the estimateTokens values for the same
// two slices.
TokensBefore int
TokensAfter int
}
// CompactorFactory mints a fresh per-run Compactor bound to a token
// threshold. onFire (nil-safe) observes every compaction that actually
// fires. A non-positive threshold yields a pass-through compactor.
type CompactorFactory func(thresholdTokens int, onFire func(CompactionEvent)) Compactor
// CompactorConfig controls the v15.2 compactor's behaviour. Construct
// in mort.go from convars + the executor's ModelResolver.
type CompactorConfig struct {
// Models resolves a model spec (typically "fast" or a specific tier)
// to an llm.Model. Required; nil disables compaction.
Models ModelResolver
// SummarizerTier is the model tier used for the compression LLM call.
// Production default "fast"; an admin may set "haiku" or a specific
// model spec. Empty falls back to "fast".
SummarizerTier string
// KeepRecent is the number of trailing messages preserved verbatim.
// Default 8. Lower values compact more aggressively (the next loop
// iteration sees less recent context); higher values keep more.
KeepRecent int
// SummaryWordCap bounds the LLM-generated summary length. Default
// 200 words ≈ 800 chars ≈ 200 tokens — small enough that the
// compaction always shrinks the slice meaningfully.
SummaryWordCap int
}
// NewCompactor returns a CompactorFactory implementing the middle-range
// summarisation strategy. nil cfg.Models returns a factory of no-op
// compactors that always return the input unchanged (degrades to
// v15.1 behaviour).
func NewCompactor(cfg CompactorConfig) CompactorFactory {
if cfg.Models == nil {
return func(int, func(CompactionEvent)) Compactor {
return func(_ context.Context, msgs []llm.Message) ([]llm.Message, error) {
return msgs, nil
}
}
}
if cfg.SummarizerTier == "" {
cfg.SummarizerTier = "fast"
}
if cfg.KeepRecent <= 0 {
cfg.KeepRecent = 8
}
if cfg.SummaryWordCap <= 0 {
cfg.SummaryWordCap = 200
}
return func(threshold int, onFire func(CompactionEvent)) Compactor {
st := &compactionState{}
return func(ctx context.Context, msgs []llm.Message) ([]llm.Message, error) {
return compactIfNeeded(ctx, cfg, st, threshold, onFire, msgs)
}
}
}
// compactionState is the per-run fold memory: msgs[:prefixEnd]
// (excluding a leading system message) are represented by summaryText
// in the rendered slice. Guarded by mu for safety although the agent
// loop invokes the hook from a single goroutine.
type compactionState struct {
mu sync.Mutex
prefixEnd int
summaryText string
}
// compactIfNeeded is the workhorse: render the transcript with any
// existing fold applied, check the threshold, and fold more of the
// middle into the summary when the rendered size still exceeds it.
func compactIfNeeded(ctx context.Context, cfg CompactorConfig, st *compactionState,
threshold int, onFire func(CompactionEvent), msgs []llm.Message) ([]llm.Message, error) {
st.mu.Lock()
defer st.mu.Unlock()
rendered := renderCompacted(st, msgs)
if threshold <= 0 {
return rendered, nil
}
tokensBefore := estimateTokens(rendered)
if tokensBefore < threshold {
return rendered, nil
}
// Determine the new middle range to fold: everything between what
// is already summarised (or the optional leading system message)
// and the KeepRecent tail.
startMiddle := st.prefixEnd
if startMiddle == 0 && len(msgs) > 0 && msgs[0].Role == llm.RoleSystem {
startMiddle = 1
}
endMiddle := len(msgs) - cfg.KeepRecent
if endMiddle <= startMiddle {
// Nothing new to fold (the tail alone exceeds the threshold).
// Return the rendered slice; the model call may still succeed.
return rendered, nil
}
middle := msgs[startMiddle:endMiddle]
summary, err := summariseMiddle(ctx, cfg, st.summaryText, middle)
if err != nil {
// Non-fatal upstream: the agent loop sends the original slice.
return rendered, fmt.Errorf("compactor: summarise middle: %w", err)
}
st.summaryText = summary
st.prefixEnd = endMiddle
out := renderCompacted(st, msgs)
if onFire != nil {
onFire(CompactionEvent{
MessagesBefore: len(rendered),
MessagesAfter: len(out),
TokensBefore: tokensBefore,
TokensAfter: estimateTokens(out),
})
}
return out, nil
}
// renderCompacted applies the fold state to msgs: [optional system] +
// [synthetic summary] + msgs[prefixEnd:]. With no fold yet, msgs is
// returned unchanged.
func renderCompacted(st *compactionState, msgs []llm.Message) []llm.Message {
if st.prefixEnd <= 0 || st.prefixEnd > len(msgs) {
return msgs
}
tail := msgs[st.prefixEnd:]
out := make([]llm.Message, 0, len(tail)+2)
if msgs[0].Role == llm.RoleSystem {
out = append(out, msgs[0])
}
out = append(out, llm.UserText(
"[CONTEXT COMPACTED] The earlier portion of this conversation was summarised "+
"to fit the model's context window. Summary:\n\n"+st.summaryText+
"\n\nResume from the recent messages below."))
out = append(out, tail...)
return out
}
// summariseMiddle composes a "compress this transcript" prompt and
// fires one fast-tier LLM call. prevSummary (may be empty) is the
// running summary from earlier compactions; it is folded into the new
// summary so prior context is not lost.
func summariseMiddle(ctx context.Context, cfg CompactorConfig, prevSummary string, middle []llm.Message) (string, error) {
if len(middle) == 0 {
return "", errors.New("compactor: empty middle range")
}
modelCtx, model, err := cfg.Models(ctx, cfg.SummarizerTier)
if err != nil {
return "", fmt.Errorf("compactor: resolve summarizer model %q: %w", cfg.SummarizerTier, err)
}
if model == nil {
return "", errors.New("compactor: summarizer model resolved to nil")
}
if modelCtx != nil {
ctx = modelCtx
}
var prior string
if strings.TrimSpace(prevSummary) != "" {
prior = "AN EARLIER PORTION WAS ALREADY SUMMARISED AS:\n" + prevSummary +
"\n\nFold that summary into your new one — its facts must survive.\n\n"
}
transcript := renderTranscript(middle)
prompt := fmt.Sprintf(
"You are compressing an in-flight agent's conversation transcript so the agent "+
"can continue working without blowing its model context. The transcript below is "+
"a sequence of tool calls and their results. Produce a single paragraph (under %d words) "+
"that captures:\n"+
" - WHAT the agent has been trying to accomplish.\n"+
" - WHICH URLs were visited / fetched (list inline, comma-separated).\n"+
" - KEY findings or decisions (factual results the agent will need later).\n"+
" - ANY file_ids or KV keys the agent created — these are persistent state references the agent must keep.\n"+
" - ANY errors or dead-ends that the agent should not re-try.\n"+
"DO NOT include verbose HTTP headers, tool-call metadata, error stack traces, or repetitive content. "+
"DO NOT add commentary or markdown headers. Output prose only.\n\n"+
"%sTRANSCRIPT TO COMPRESS:\n%s",
cfg.SummaryWordCap,
prior,
transcript,
)
resp, err := model.Generate(ctx, llm.Request{Messages: []llm.Message{llm.UserText(prompt)}})
if err != nil {
return "", fmt.Errorf("compactor: summarise LLM call: %w", err)
}
text := strings.TrimSpace(resp.Text())
if text == "" {
return "", errors.New("compactor: summarizer returned empty text")
}
return text, nil
}
// estimateTokens is the chars/4 heuristic over a message slice's text,
// tool calls, and tool results. Images count a flat ~1K tokens each.
// It intentionally matches the coarse estimator the old agentkit loop
// used — the 0.7 threshold ratio provides the safety margin.
func estimateTokens(msgs []llm.Message) int {
chars := 0
for _, m := range msgs {
for _, p := range m.Parts {
switch v := p.(type) {
case llm.TextPart:
chars += len(v.Text)
case llm.ImagePart:
chars += 4096
}
}
for _, tc := range m.ToolCalls {
chars += len(tc.Name) + len(tc.Arguments)
}
for _, tr := range m.ToolResults {
chars += len(tr.Content)
}
}
return chars / 4
}
// transcriptMessageCap bounds individual message bodies at ~2KB so a
// single ultra-long tool result can't dominate the prompt sent to the
// summarizer.
const transcriptMessageCap = 2048
// renderTranscript flattens a message slice to a plain-text transcript
// suitable for the summarisation prompt. Tool calls show name + args,
// tool results show name + body. Empty fields are skipped.
func renderTranscript(msgs []llm.Message) string {
var sb strings.Builder
for i, m := range msgs {
fmt.Fprintf(&sb, "---\n[%d] role=%s\n", i+1, m.Role)
if text := m.Text(); text != "" {
sb.WriteString(truncate(text, transcriptMessageCap))
sb.WriteString("\n")
}
for _, tc := range m.ToolCalls {
fmt.Fprintf(&sb, "tool_call name=%s args=%s\n", tc.Name, truncate(string(tc.Arguments), transcriptMessageCap))
}
for _, tr := range m.ToolResults {
fmt.Fprintf(&sb, "tool_result name=%s body=%s\n", tr.Name, truncate(tr.Content, transcriptMessageCap))
}
}
return sb.String()
}
func truncate(s string, n int) string {
if len(s) <= n {
return s
}
return s[:n] + "...(truncated)"
}
+407
View File
@@ -0,0 +1,407 @@
package run
// steps.go — the per-run step emitter and the tool→step presentation
// mapping. This is the single place that turns the executor's two loop
// chokepoints (the pre-dispatch tool hook + the post-step observer in
// executor.go) into ordered tool.Step records: one per tool call,
// each with a stable id, an open-vocabulary kind, and a human
// present-tense summary that flips running→complete/error.
//
// One source feeds two consumers (mirroring the OnEvent/OnToolEvent/
// PostRunResult pattern): the live tool.Invocation.OnStep callback
// (nil-safe) AND snapshot(), which the executor copies onto Result.Steps.
// Because the Result accumulation does not depend on OnStep being set,
// every surface — chat (JSON + SSE), Discord, cron, sub-agents — carries
// steps; OnStep is needed only for live streaming.
import (
"context"
"encoding/json"
"fmt"
"net/url"
"strings"
"time"
"gitea.stevedudenhoeffer.com/steve/majordomo/llm"
"gitea.stevedudenhoeffer.com/steve/executus/tool"
)
// stepSummaryMaxLen caps the human summary length (section G size cap).
// Detail is unused in v1 (no live detail source while replies are
// generated blocking) so there is no Detail cap yet.
const stepSummaryMaxLen = 200
// stepEmitter accumulates ordered steps for one run and fires the live
// OnStep callback.
//
// Concurrency: touched ONLY from the agent-loop goroutine. Both call
// sites (the hookToolbox `before` closure and the stepObserver) run
// there; majordomo executes a step's tool calls sequentially, and
// sub-agents build their own Invocation so they never reach this
// emitter. Same single-goroutine contract as the audit Writer and the
// critic ProgressRecorder — no internal lock.
type stepEmitter struct {
onStep func(ctx context.Context, ev tool.StepEvent)
now func() time.Time
seq int
steps []tool.Step // ordered; the snapshot for Result.Steps
byID map[string]int // step id -> index into steps
pending map[string][]string // correlation key -> queued running ids (FIFO)
}
// newStepEmitter returns an emitter that forwards to onStep (nil-safe).
func newStepEmitter(onStep func(ctx context.Context, ev tool.StepEvent)) *stepEmitter {
return &stepEmitter{
onStep: onStep,
now: time.Now,
byID: map[string]int{},
pending: map[string][]string{},
}
}
// corrKey correlates a "start" (name + raw args, no call id available at
// the pre-dispatch hook) with its later "end" (the stepObserver has the
// full call incl. id + the same raw args).
func corrKey(name string, args json.RawMessage) string {
return name + "\x00" + string(args)
}
// toolStart records + emits the "start" of a tool call. Called from the
// pre-dispatch hookToolbox closure, before the tool runs.
func (e *stepEmitter) toolStart(ctx context.Context, name string, args json.RawMessage) {
if e == nil {
return
}
step := e.newStep(name, args)
key := corrKey(name, args)
e.pending[key] = append(e.pending[key], step.ID)
e.fire(ctx, "start", step)
}
// toolEnd records + emits the terminal "end" of a tool call. Called from
// the stepObserver for each completed tool call. If no matching start was
// seen (e.g. a tool with a nil handler the pre-dispatch hook skipped), a
// start is synthesized so the step still appears.
func (e *stepEmitter) toolEnd(ctx context.Context, call llm.ToolCall, result string, isError bool) {
if e == nil {
return
}
id := e.matchPending(call.Name, call.Arguments)
if id == "" {
id = e.newStep(call.Name, call.Arguments).ID
}
idx, ok := e.byID[id]
if !ok {
return
}
step := &e.steps[idx]
end := e.now()
step.EndedAt = &end
if isError {
step.Status = "error"
} else {
step.Status = "complete"
}
if s := summaryForEnd(call.Name, call.Arguments, result, isError); s != "" {
step.Summary = s
}
e.fire(ctx, "end", *step)
}
// newStep mints + appends a running step and returns it (by value).
func (e *stepEmitter) newStep(name string, args json.RawMessage) tool.Step {
e.seq++
step := tool.Step{
ID: fmt.Sprintf("s%d", e.seq),
Kind: kindForTool(name),
Title: name,
Summary: summaryForStart(name, args),
Status: "running",
StartedAt: e.now(),
}
e.byID[step.ID] = len(e.steps)
e.steps = append(e.steps, step)
return step
}
// matchPending pops the oldest running step id for (name, args). Falls
// back to the most recent still-running step of the same tool name when
// the args don't byte-match between start and end. Returns "" on no match.
func (e *stepEmitter) matchPending(name string, args json.RawMessage) string {
key := corrKey(name, args)
if q := e.pending[key]; len(q) > 0 {
id := q[0]
if len(q) == 1 {
delete(e.pending, key)
} else {
e.pending[key] = q[1:]
}
return id
}
for i := len(e.steps) - 1; i >= 0; i-- {
if e.steps[i].Title == name && e.steps[i].Status == "running" {
return e.steps[i].ID
}
}
return ""
}
func (e *stepEmitter) fire(ctx context.Context, phase string, step tool.Step) {
if e.onStep == nil {
return
}
e.onStep(ctx, tool.StepEvent{Phase: phase, Step: step})
}
// snapshot returns a copy of the ordered, deduplicated step set for the
// run Result. A step still "running" at run end (e.g. the run was
// cancelled mid-tool-call) is reported as-is.
func (e *stepEmitter) snapshot() []tool.Step {
if e == nil || len(e.steps) == 0 {
return nil
}
out := make([]tool.Step, len(e.steps))
copy(out, e.steps)
return out
}
// kindForTool maps a tool name to an open-vocabulary step kind. Unknown
// tools fall back to "tool" — never an error, just a generic step (the
// client maps unknown kinds to a default icon). Loosely tracks the
// catalog in pkg/skilltools/CLAUDE.md.
func kindForTool(name string) string {
switch name {
case "web_search", "search_reddit", "wikipedia_summary":
return "search"
case "read_page", "read_pdf", "read_reddit", "read_video", "verify_url",
"summary_summarise", "summarize", "file_get_text", "file_get_metadata",
"http_get", "http_post", "http_get_stream", "http_stream_read":
return "read"
case "code_exec", "calculate":
return "code"
case "file_save", "file_get", "file_list", "file_delete", "file_search":
return "file"
case "kv_get", "kv_set", "kv_list", "kv_delete",
"remember", "recall", "chatbot_get_memories":
return "memory"
case "query", "query_research", "deepresearch", "animate",
"agent_invoke", "agent_invoke_parallel", "agent_spawn",
"agent_spawn_parallel", "skill_invoke", "skill_invoke_parallel":
return "delegate"
case "think":
return "thinking"
default:
switch {
case strings.HasPrefix(name, "image") || strings.Contains(name, "draw"):
return "image"
default:
return "tool"
}
}
}
// summaryForStart builds the human present-tense running summary. It
// derives specifics from safe arg fields only; secret-bearing tools
// (mcp_call, email_send, http_*) are summarized without echoing args.
func summaryForStart(name string, args json.RawMessage) string {
var s string
switch name {
case "web_search":
if q := argString(args, "query", "q"); q != "" {
s = fmt.Sprintf("Searching the web for %q", q)
} else {
s = "Searching the web"
}
case "search_reddit":
if q := argString(args, "query", "q"); q != "" {
s = fmt.Sprintf("Searching Reddit for %q", q)
} else {
s = "Searching Reddit"
}
case "wikipedia_summary":
if q := argString(args, "query", "title"); q != "" {
s = fmt.Sprintf("Looking up %q on Wikipedia", q)
} else {
s = "Looking up Wikipedia"
}
case "read_page", "read_pdf", "read_reddit", "read_video", "verify_url":
if u := argString(args, "url", "post", "page"); u != "" {
s = "Reading " + hostOf(u)
} else {
s = "Reading a page"
}
case "http_get", "http_post", "http_get_stream":
// Show host only — a full URL can embed credentials/tokens.
if u := argString(args, "url"); u != "" {
s = "Fetching " + hostOf(u)
} else {
s = "Making an HTTP request"
}
case "summary_summarise", "summarize":
s = "Summarizing text"
case "translate":
if lang := argString(args, "target_lang", "target_language", "lang"); lang != "" {
s = "Translating to " + lang
} else {
s = "Translating text"
}
case "code_exec":
s = "Running code"
case "calculate":
if q := argString(args, "query", "expression", "expr"); q != "" {
s = "Calculating " + truncateStep(q, 60)
} else {
s = "Calculating"
}
case "remember":
// Never echo the stored value.
s = "Saving a memory"
case "recall", "chatbot_get_memories":
s = "Recalling memories"
case "kv_get", "kv_list":
s = "Reading saved data"
case "kv_set":
s = "Saving data"
case "kv_delete":
s = "Deleting saved data"
case "file_save":
if n := argString(args, "name", "filename"); n != "" {
s = "Saving file " + truncateStep(n, 60)
} else {
s = "Saving a file"
}
case "file_get", "file_get_text", "file_get_metadata":
s = "Reading a file"
case "file_list", "file_search":
s = "Listing files"
case "query", "query_research":
if q := argString(args, "query", "question", "prompt", "task"); q != "" {
s = "Researching " + truncateStep(q, 80)
} else {
s = "Researching"
}
case "deepresearch":
s = "Running deep research"
case "animate":
s = "Generating an animation"
case "agent_invoke", "agent_spawn":
if a := argString(args, "agent", "agent_name", "name"); a != "" {
s = "Delegating to " + a
} else {
s = "Delegating to a sub-agent"
}
case "agent_invoke_parallel", "agent_spawn_parallel":
s = "Delegating to sub-agents"
case "skill_invoke":
if sk := argString(args, "skill_name", "skill", "name"); sk != "" {
s = "Running skill " + sk
} else {
s = "Running a skill"
}
case "skill_invoke_parallel":
s = "Running skills in parallel"
case "think":
s = "Thinking"
case "mcp_call":
// Redact: MCP args frequently carry secrets. Name server/tool only.
srv, tl := argString(args, "server"), argString(args, "tool")
switch {
case srv != "" && tl != "":
s = fmt.Sprintf("Calling %s/%s", srv, tl)
case srv != "":
s = "Calling " + srv
default:
s = "Calling an MCP tool"
}
case "email_send":
// Redact recipients + body.
s = "Sending an email"
default:
s = "Using " + name
}
return truncateStep(s, stepSummaryMaxLen)
}
// summaryForEnd optionally upgrades the summary to a cheap result phrase.
// Returns "" to keep the running summary (the caller then just flips the
// status). Never returns a phrase derived from raw result bytes.
func summaryForEnd(name string, _ json.RawMessage, result string, isError bool) string {
if isError {
return ""
}
switch name {
case "web_search", "search_reddit":
if n := countResults(result); n >= 0 {
return fmt.Sprintf("Found %d result%s", n, plural(n))
}
}
return ""
}
// argString pulls the first present non-empty string field from a tool's
// raw JSON args, trying keys in order. Returns "" when none parse.
func argString(args json.RawMessage, keys ...string) string {
if len(args) == 0 {
return ""
}
var m map[string]any
if err := json.Unmarshal(args, &m); err != nil {
return ""
}
for _, k := range keys {
if v, ok := m[k]; ok {
if s, ok := v.(string); ok && strings.TrimSpace(s) != "" {
return strings.TrimSpace(s)
}
}
}
return ""
}
// countResults parses a v11-style {"results":[...]} envelope and returns
// the count, or -1 when the shape doesn't match.
func countResults(result string) int {
if strings.TrimSpace(result) == "" {
return -1
}
var env struct {
Results []json.RawMessage `json:"results"`
}
if err := json.Unmarshal([]byte(result), &env); err != nil || env.Results == nil {
return -1
}
return len(env.Results)
}
// hostOf returns the bare host (no leading www.) of a URL, or a short
// form of the raw string when it doesn't parse as a URL.
func hostOf(raw string) string {
if u, err := url.Parse(raw); err == nil && u.Host != "" {
return strings.TrimPrefix(u.Host, "www.")
}
return truncateStep(raw, 60)
}
// truncateStep rune-safely caps s to max, appending an ellipsis when cut.
func truncateStep(s string, max int) string {
if max <= 0 {
return ""
}
r := []rune(s)
if len(r) <= max {
return s
}
if max == 1 {
return string(r[:1])
}
return string(r[:max-1]) + "…"
}
func plural(n int) string {
if n == 1 {
return ""
}
return "s"
}