Continuity, measured

Pick up the work.
Spend less getting there.

Crosshead gives your next Claude Code or Codex session the context to keep going. See how automatic continuity performs on task completion and model API cost.

Free working memory. Tested with GPT-6.1 Sol and Claude Opus 5.5. Compare ways to continue your work.

Fresh sessions · Switching tools · Compaction · Native resume

104 trials · eight task families · two coding tools

Fresh sessions: finish the work for less.

Crosshead completed 16/16 workflows for $1.62 in model API costs. The tasks tested exact requirements, corrections, conflicting evidence and interrupted work.

62% lower API cost

Than claude-mem, with both completing all 16 workflows.

67% lower API cost

Than Cairntir, with both completing all 16 workflows.

Automatic capture

Keep the task moving without writing your own handoff. Crosshead also cost 13.7% less than the update-only handoff control.

The same 16 fresh-session workflows per method: eight in Codex and eight in Claude Code. Total model API cost in USD, including capture and recall.
MethodWorkflows completedTotal API cost
Crosshead16/16$1.62
Agent-written handoff · updated when needed16/16$1.88
Structured handoff + saved sources16/16$2.22
Cairntir16/16$4.92
claude-mem16/16$4.29
Supermemory Local · configured11/16$2.89

25% lower API cost than Claude Code auto memory

In the separate Claude-only comparison, both methods completed 8/8 fresh-session workflows. Crosshead cost $0.91; auto memory cost $1.21. Auto memory carries saved notes into a fresh session; resuming an existing conversation is a different workflow.

Eight synthetic task families created by Crosshead, using GPT-6.1 Sol and Claude Opus 5.5. One run per task and tool pairing. Costs include coding and background model calls; subscriptions, service fees, local compute and operator time are excluded.

This comparison starts a fresh session within the same tool. See the separate switching-tools results below.

Download the fresh-session results and evidence · How the comparison works

Test design, configurations and supporting evidence
Results by coding tool
Successful workflows / attempts, with total API cost in USD for each column.
MethodFresh CodexFresh Claude Code
Crosshead8/8
$0.71
8/8
$0.91
Agent-written handoff · updated when needed8/8
$0.80
8/8
$1.08
Structured handoff + saved sources8/8
$0.98
8/8
$1.24
Cairntir8/8
$1.69
8/8
$3.24
claude-mem8/8
$1.64
8/8
$2.66
Supermemory Local · configured5/8
$1.09
6/8
$1.80
Claude Code auto memory—8/8
$1.21
Models, integrations and equal access to evidence

Both coding models use medium reasoning effort through Codex codex-cli 0.159.3 and Claude Code 2.1.302 (Claude Code). Every method receives the same instructions and original source access in isolated workspaces. Source files disappear before continuation; each method can preserve them through its supported memory or handoff mechanism. Fresh sessions cannot recover the old transcript.

Crosshead uses real automatic hooks and free local hot memory. The agent-written control maintains up to 500 words, updated only when relevant facts change. The structured control can retain 6,000 characters of task state and six source excerpts totaling 12,000 characters through ordinary file writes and retrieval. Crosshead has the same retained-source budget and a 4,200-character automatic delivery budget.

Cairntir 1.12.3 and claude-mem 14.0.1 use their official integrations and local default embeddings. Claude Code auto memory runs with its native instructions enabled. Each coding session has one CPU, 2 GiB of RAM, no swap and 180 seconds. Background capture can take up to 140 seconds for claude-mem and 600 seconds for Supermemory Local. Capture and fresh recall are verified before scored trials.

Supermemory Local configuration

Supermemory Local 0.0.9 uses official Codex 1.0.21 and Claude Code 0.1.13 plugins, GPT-5.1 extraction, v5 REST, instant processing and synchronous capture. These settings support one-shot CLI sessions. Hosted Supermemory is a separate service and was not measured here. Every background extraction call counts toward cost, including OpenAI calls during Claude trials. All five unsuccessful workflows remain in the results.

Cost differences and uncertainty
Crosshead API-cost savings against matched methods. Descriptive 95% intervals resample task families.
MethodLower API cost95% family interval
Structured handoff + saved sources27.0%23.0% to 31.3%
Supermemory Local · configured44.0%40.5% to 47.2%
Agent-written handoff · updated when needed13.7%9.6% to 17.6%
claude-mem62.3%61.3% to 63.4%
Cairntir67.1%63.7% to 70.2%
Claude Code auto memory24.9%17.2% to 32.2%

Native memory is paired only with the same eight Claude workflows. These are vendor-authored synthetic tasks, not an independent holdout or a production success-rate estimate. One repeat and perfect observed scores do not prove equal reliability across future work.

Capture, delivery and task success

Automatic capture preserves the request, observed source excerpts and assistant findings separately. Same-task updates retain prior decisions; conflicting observations remain visible. Capture and delivery are bounded, and incomplete excerpts are marked.

At 20 continuation boundaries, 0 immediately preceding excerpts and 4 excerpts from earlier sessions were not delivered in full. The downloadable audit retains these observations separately from task scores. A passing task does not certify complete retention, and an omitted earlier excerpt is not automatically a missing requirement.

Collection scope and reproducibility

All 104 planned same-tool observations are included, regardless of outcome. The 128-trial execution also contains cross-tool comparisons; 12 of those remain unrun. This publication covers the completed same-tool lane and makes no cross-tool ranking from it. Candidate, model settings and scoring stayed fixed; the product was not tuned on these results.

The scoped-correction prompt was clarified to distinguish loss of source-file access from expiry of the requirements. Every observation for that family was replaced across methods and hosts, including passes. Original outcomes, transport interruptions, the zero-cost integration setup correction and all retained charges remain in the download. No valid task failure was dropped.

A handoff has to earn its place.

Do the work

An agent investigates a task, reads its requirements and encounters changes or interruptions. Each method gets the same starting evidence.

Start a fresh session

The next agent gets the working files and the method’s saved context. Some workflows also switch between Claude Code and Codex.

Check the outcome

Hidden tests check the finished work. We count the API cost of every session and any background capture, then inspect what reached the next agent.

Switch tools · six tasks · two repeats · both directions

From Codex to Claude Code. And back.

Crosshead completed 12/12 workflows in each direction, matching written handoffs, at 21–22% lower API cost. Cold restarts completed 8/12 in each direction.

Keep the investigation moving in one tool and implement in the other. Crosshead carries working context across the switch automatically.

This six-task regression comparison uses a handoff written at every session boundary. Its savings apply to that control; the fresh-session comparison above uses handoffs updated only when needed.

Switching tools: results and method
72 cross-tool trials; total API cost includes both providers
Model / directionMethodPassedInput + output tokensAPI cost (USD)
GPT → ClaudeCold restart8/121,041,337$1.07
GPT → ClaudeWritten handoff12/121,250,118$1.34
GPT → ClaudeCrosshead · fresh session12/121,034,465$1.05
Claude → GPTCold restart8/121,155,509$1.12
Claude → GPTWritten handoff12/121,127,693$1.45
Claude → GPTCrosshead · fresh session12/12971,141$1.13

Crosshead used 17.3% fewer tokens and cost 21.5% less for GPT → Claude; 13.9% fewer tokens and 22.0% less for Claude → GPT. The task-bootstrap cost-savings intervals were 16.9–26.5% and 17.3–26.8%, respectively. Native resume cannot continue the other tool’s conversation. These development tasks were available during product fixes.

Download switching, resume and compaction results.

Keep context through compaction · two-task pilot

Keep the task through a shorter context.

Crosshead completed 4/4 workflows through two native compactions and 4/4 with fresh sessions. Update-only handoffs also completed all four fresh-session cases.

In the fresh sessions, Crosshead cost 5.9% less on GPT and 10.3% less on Claude than those update-only handoffs.

A controlled two-task pilot with manual compaction and outside-workspace transcript recovery disabled. It tests retained context under those conditions; default automatic compaction and dynamic timing remain unmeasured.

Compaction: results and method
16 trials with verified Crosshead hooks; one repeat; update-only handoffs
Model / directionMethodPassedInput + output tokensAPI cost (USD)
GPT-6.1 SolNative compaction2/21,532,821$0.93
GPT-6.1 SolCrosshead + native compaction2/21,386,720$0.88
GPT-6.1 SolWritten handoff2/21,681,919$1.04
GPT-6.1 SolCrosshead · fresh session2/21,462,747$0.98
Claude Opus 5.5Native compaction1/2931,194$2.94
Claude Opus 5.5Crosshead + native compaction2/21,138,668$3.27
Claude Opus 5.5Written handoff2/21,127,826$1.84
Claude Opus 5.5Crosshead · fresh session2/2658,702$1.65

We tested a disappearing behavior contract and a corrected contract, with two large irrelevant logs between investigation and implementation. Resumed conditions used real native manual compaction twice. Fresh-session conditions kept Crosshead memory or a handoff note updated only when relevant facts changed. Context pressure stayed below the default full-window threshold.

Native compaction passed 3/4 under the transcript restriction; the failed Claude case lost exact contract rules. With same-session transcript recovery allowed in a targeted follow-up, Claude retrieved the contract and passed ($1.57). That diagnostic was selected after the failure and is excluded from comparison rates.

The records retain calibration attempts and two Codex runs affected by skipped compaction hooks. Both Codex cases were rechecked with verified hooks; all attempts count toward the campaign budget. Two regression tasks do not establish a general success rate or an optimal compaction point.

Download compaction evidence.

Continue the conversation, or start fresh · 24 tasks · two repeats

A fresh thread can still finish the work.

Crosshead completed 48/48 workflows on each model, matching native resume and written handoffs. Cold restarts completed 38/48 on each.

Resume is a good choice when you want to continue the existing conversation in the same tool. It cost less in this comparison: Crosshead used 17.4% more API spend on Claude and 58.1% more on GPT. Crosshead gives you continuity when you want a fresh thread or a different coding tool.

Native resume: results and method
384 trials; total model API cost includes investigation and continuation
Model / directionMethodPassedInput + output tokensAPI cost (USD)
Claude Opus 5.5Cold restart38/482,749,605$3.81
Claude Opus 5.5Written handoff48/483,406,591$5.49
Claude Opus 5.5Native resume48/482,494,588$3.31
Claude Opus 5.5Crosshead · fresh session48/482,675,191$3.89
GPT-6.1 SolCold restart38/485,577,704$4.23
GPT-6.1 SolWritten handoff48/486,011,964$4.81
GPT-6.1 SolNative resume48/484,962,301$2.64
GPT-6.1 SolCrosshead · fresh session48/485,108,872$4.17

These synthetic development/regression tasks were used during memory fixes. The written control saves up to 500 words at every boundary, including unrelated interludes. Native resume retains the original conversation; a cold restart receives only workspace state.

The campaign retains 480 comparison records: 384 main trials, 72 switching trials and 24 quota rechecks. Eight main trials were interrupted by an Anthropic quota outage. All methods and repeats for the three affected families were rechecked, including passes; the displayed totals use those complete replacement blocks.

Download native-resume results.

Inspect the evidence.

Each comparison answers a different workflow question. Results include model API usage, with cached input counted once and reasoning included in output. Service fees, subscriptions, local compute and operator time are excluded. Task success and context delivery are checked separately.

These are vendor-authored synthetic tasks. Sample sizes, controls and runtime versions differ by comparison; the records below identify each frozen configuration. They help you assess the tested workflows, rather than predict a production success rate.

Downloadable results and versioned run records

Deterministic public and hidden tests score behavior, with integrity checks protecting the tests. Outgoing requests verify Crosshead delivery. Runtime, fixture and scorer hashes are frozen for each campaign; results from different campaigns are not pooled.

Your next session can start ready. Give your agent continuity.