earakely-scale/SentryEnv-REA

sentry

sentry

An AgentEnv bundle with its recorded runs, published with agentenv-hf.

Tables

• sentry_tasks: one row per task of the bundle, with its prompt, envs, verifiers and steps.
• sentry_episodes: one row per recorded run, with its status, model, reward and scores, the prompt and response, and the agent's transcript as chat messages when its trajectory format is one agentenv-hf reads.

raw/sentry.jsonl holds each run's record and native trajectory, and bundles/sentry/ the bundle itself.

Run it

pip install agentenv-framework huggingface_hub
hf download earakely-scale/SentryEnv-REA --repo-type dataset --local-dir agentenv-dataset
agent-env run agentenv-dataset/bundles/sentry

Sentry on AgentEnv, from a REA capture

What this is. An environment of Sentry 26.9.0 (FSL-1.1-Apache-2.0), built from one recorded browser session against a self-hosted instance seeded with synthetic data. REA projected the capture into an environment manifest (34 tools) and an environment state, the entities the capture's reads showed, and rea environment-export wrote the bundle you can run from this dataset. Reads the state can render are answered from it, write tools whose effect the capture confirmed change it, and data/reset restores it. Nothing executes Sentry. Tasks are graded deterministically, with no judge.

v0.2.0 rebuilds this environment from the same capture with a REA build that serves a state and confirmed writes; the tag v0.1.0 keeps the earlier replay-only version.

What's in it

• 34 tools (29 GET, 2 PUT, 2 POST, 1 DELETE) over 72 recorded exchanges on http://127.0.0.1:3301; no recorded group excluded. 32 are offered; the other 2 are write tools the environment cannot apply (put_organizations_sentry_issues_by_id_id_2, post_organizations_sentry_issues_comments_by_id_id_2), left out rather than faked.
• Path parameters: 45 numeric, 2 prefix-variance, 2 sibling-variance, 1 hex. REA's four format rules (numeric, uuid, hex, iso-date) applied unconditionally; the four opt-in rules (after-uid-literal, opaque-token, sibling-variance, prefix-variance) were requested and are labelled per parameter. With the four format rules alone the manifest has 37 tools.
• State: 62 entities of 17 types. 26 read tools answer from it and 3 replay their recorded responses. Served write tools: post_organizations_sentry_releases_by_id (create), delete_organizations_sentry_releases_by_id_release_id (delete), put_organizations_sentry_releases_by_id_release_id (update).
• Unknowns the manifest states explicitly: authorization model, response semantics beyond recorded exchanges, state transitions between tools.
• 12 retrieval tasks (evals/sentry-retrieval.toml): each asks one factual question about a seeded object, with a distinct answer that the app does not ship by default; reward 1 if the response contains the recorded value, else 0. Plus smoke, which deploys the environment and checks it through the MCP endpoint.
• 4 write tasks (evals/sentry-writes.toml): each asks for a change in plain language and is graded from the environment's state through data/get, not from the agent's reply; reward 1 only if every check passes. Their grade is in scores.state; reward holds the retrieval verifier's score, so it is empty for them, as for smoke.
• 24 retrieval episodes and 12 write episodes, plus the smoke run, by openai/gpt-oss-120b:groq, zai-org/GLM-5.3-Flash:zai-org through the Hugging Face router, with their chat transcripts.
• Provenance: capture ev_5d1ae1d1e71bdfa98a8f7124d3afb2acb81fbaad4eb7dcd625c754a2a5e316e5 (scoped HAR sha256 ef68ab559bb35e106737bbe34c0e0442a12bcf8add0d65385775dda66e9486e4, 419,121 bytes), manifest view ev_5d82219cd5a8791dddf10e8b05cc4da3481436dd3fdc201a4988f821f09e0c3a, confidence inferred, authority historical-reference. The REA build is rea-agents 6.7.0 from main 1629266e with open pull requests merged: morluto/rea#5600 at 370b9bef (which carries #5351 and #5352) and #5664 at 930c96d0. The bundle installs it from the tarball it ships, so the environment runs without waiting for an npm release.

What the state means, and does not

Reads the state can render, item, list and document views of the entities the capture's responses showed, answer from it. Other reads replay the recorded response whose path and query values best match the arguments, with replay.exact_match saying whether it matched exactly; a replayed read does not change after a write. A served write was confirmed by the capture itself: replaying the session against the extracted state, a later recorded read reproduced its effect and none contradicted it. A create generates ids and clock values deterministically, so the same calls after a reset give the same state; an update changes the members the call sends; a delete removes the entity. Each takes only the body members the recorded call showed and refuses others with a message that names the accepted ones. Its effect shows in the reads the state renders, except that a list the capture saw only filtered or in part keeps its recorded members: it drops a deleted entity but does not add a new one. The data plane at /agentenv takes data/reset (restore the extracted state), data/add and data/get (return it), which is how write tasks are graded.

Not modelled: side effects a write has beyond its own entity (counters, copies in other collections, related entities), preconditions the application enforces before a write, new entities in lists whose recorded calls were filtered, and anything the capture never showed. The manifest's unknowns list what a capture cannot establish.

Tasks and grading

Retrieval

task	tool	arguments	field	answer
qa-01-get_organizations_sentry_issues_by_id_id	get_organizations_sentry_issues_by_id_id_2	id=0, id_2=1	firstRelease.lastDeploy.name	Tide window rollout at 22:00
qa-02-get_projects_sentry_copperfield_annex_ap	get_projects_sentry_copperfield_annex_api_rules_by_id_id_2	id=0, id_2=1	name	Granite Ledger tally drift alert
qa-03-get_projects_sentry_saltmarsh_depot_scan	get_projects_sentry_saltmarsh_depot_scanner_rules_by_id_id_2	id=0, id_2=2	conditions[0].name	A new issue is created
qa-04-get_organizations_sentry_releases_by_id	get_organizations_sentry_releases_by_id	id=0, per_page=10	[0].userAgent	Python-urllib/3.12
qa-05-get_organizations_sentry_releases_deploy	get_organizations_sentry_releases_deploys_by_id_release_id	id=0, release_id=blue-heron-orders%401.9.0	[0].name	Kelp broth menu dry run
qa-06-get_organizations_sentry_issues_events_b	get_organizations_sentry_issues_events_by_id_id_2	id=0, id_2=1, limit=5	[0].user.username	ada.finch
qa-07-get_projects_sentry_saltmarsh_depot_scan	get_projects_sentry_saltmarsh_depot_scanner_events_by_id_has	id=0, hash=de8079d0fc3748f3b027dfa59ef02e11	release.lastDeploy.name	Conveyor seven firmware swap
qa-08-get_organizations_sentry_dashboards_by_i	get_organizations_sentry_dashboards_by_id_id_2	id=0, id_2=1	title	Quarry Gate Error Watch
qa-09-get_organizations_sentry_dashboards_by_i	get_organizations_sentry_dashboards_by_id	id=0	[0].title	Blue Heron Kitchen Service Board
qa-10-get_projects_sentry_copperfield_annex_ap	get_projects_sentry_copperfield_annex_api_rules_by_id	id=0	[0].owner	team:2
qa-11-get_organizations_sentry_members_by_id_i	get_organizations_sentry_members_by_id_id_2	id=0, id_2=2	email	ada.finch@example.test
qa-12-get_organizations_sentry_issues_by_id	get_organizations_sentry_issues_by_id	id=0, query=is:unresolved, statsPeriod=14d, limit=25	[0].title	LedgerMismatchError: Granite Ledger tally off by 3 blocks at quarry gate B

Writes

Graded from the environment's state through data/get (scores.state in the episodes table; reward 1 only if every check passes).

task	prompt	checks
write-create	In this Sentry organization, create a new release with version "lighthouse-rota-web@3.1.0" for the project lighthouse-rota-web.	a release lighthouse-rota-web@3.1.0 exists; it belongs to lighthouse-rota-web; the four seeded releases are still there
write-update	In this Sentry organization, set the ref of the release copperfield-annex-api@2.4.1 to "dock-shift-handover".	copperfield-annex-api@2.4.1 has ref dock-shift-handover; no other release ref changed; no release was added or removed
write-delete	In this Sentry organization, delete the release saltmarsh-depot-scanner@0.7.3, and only that release.	saltmarsh-depot-scanner@0.7.3 is gone; the other three releases remain
write-create-then-update	In this Sentry organization, create a release "lighthouse-rota-web@3.1.1" for the project lighthouse-rota-web, then set that new release's ref to "tide-tables".	the release exists; its ref is tide-tables; exactly one release was added

Episodes

model	retrieval episodes	passed	pass rate	mean tool calls	mean input tokens
openai/gpt-oss-120b:groq	12	12	100%	1.1	19,194
zai-org/GLM-5.3-Flash:zai-org	12	11	92%	1.7	29,580

Every episode is in the episodes config with its transcript; scores are the deterministic verifier scores.

model	write episodes	passed
openai/gpt-oss-120b:groq	8	2
zai-org/GLM-5.3-Flash:zai-org	4	4

GLM-5.3-Flash missed qa-03-get_projects_sentry_saltmarsh_depot_scan: it never called the alert-rules tool and answered that no tool exposes the value. gpt-oss-120b ran the write eval twice and passed 2 of 8 episodes: in every failed one it passed id: "sentry" for the /api/0/ path segment, which the tool schema describes as observed: 0, so its calls addressed releases the state does not hold; its passing episodes, and every GLM-5.3-Flash episode, passed 0.

Run it yourself

uv tool install agentenv-framework --with 'agentenv-hf @ git+https://github.com/earakely-scale/agentenv-hf-plugin@v0.3.0'
agent-env hf run earakely-scale/SentryEnv-REA --bundle sentry --task smoke          # Docker, no model
agent-env hf run earakely-scale/SentryEnv-REA --bundle sentry --eval sentry-retrieval --model openai/gpt-oss-120b:groq
agent-env hf run earakely-scale/SentryEnv-REA --bundle sentry --eval sentry-writes --model openai/gpt-oss-120b:groq

The evals need a model endpoint: set [model] base_url and api_key in .agentenv/config.toml (the Hugging Face router works with any hf_ token). The bundle's agents/replay-qa is a small OpenAI-compatible tool-calling agent; any A2A agent can replace it.

How it was made

1. Sentry ran in Docker on a throwaway VM, bound to loopback, seeded through its own API with synthetic records (an organization renamed Lighthouse Rota with 3 teams, 4 projects, 4 releases with 4 deploys, 4 invited members, 12 invented error events grouped into 8 issues (2 with notes, one assigned to a team, one resolved, one bookmarked), 2 issue alert rules and 2 dashboards); people and projects are invented.
2. Playwright drove a login, the main pages and a scripted read, write, read sequence through the app's JSON API; the HAR was scoped to the API, the login exchange dropped, secret-looking body fields scrubbed, headers and cookies removed.
3. rea inspect-web-network-capture retained the exchanges as Evidence; rea inspect-analysis-view projected the environment-manifest view; rea environment-export wrote this bundle and the state it serves; gen_tasks.py derived the retrieval tasks from the manifest and the recorded bodies; the write tasks were written by hand against the served write tools and the seeded names; agent-env run recorded the episodes; agent-env hf publish wrote this dataset. Scripts: https://github.com/earakely-scale/rea-environments.

Compared with PortSimEnv on AgentEnv

	PortSimEnv-AgentEnv	Sentry (this dataset)
Environment	A simulation: a container quay, ships, cranes, weather, with A2A ship agents	An application's API rebuilt from one captured session
Observation	Tool results computed by the simulator as the week unfolds	Answers rendered from the extracted state, or recorded responses, cited to Evidence
Action space	Planning tools (check_plan, confirm_berths, advance, message_agent)	32 tools mirroring the application's endpoints
State	Full: a virtual clock, triggers, frozen windows, agents that answer	A state extracted from the capture (62 entities); served writes change it; data/reset restores it
Reward	Deterministic, against a CP-SAT optimum or a re-planner anchor; continuous 0 to 1	Deterministic: recorded-value match for retrieval, state checks for writes; 0 or 1 per task
What it measures	Planning under uncertainty and negotiation	Tool discovery, parameter inference and faithful retrieval in a real API, and changing its state
Data provenance	Real 2024 port calls and weather; simulated workloads	Synthetic seed data on a self-hosted Sentry; nothing real
How it was built	Hand-written plugin, months of work	Generated from a capture in one scripted pass
Where it is strong	Long-horizon decisions with hard rewards	Breadth: any app you can capture becomes an environment

The two are complementary: PortSimEnv shows what a hand-built simulation can grade; this dataset shows how far a capture alone gets you, and the manifest's unknowns and the state's limits above say what it still leaves out.

Licence and credits

Bundle code and tasks: Apache-2.0. Recorded content: responses generated by a self-hosted Sentry instance over synthetic data; Sentry is FSL-1.1-Apache-2.0 software by Functional Software, Inc. (Sentry) and is not redistributed here beyond the recorded JSON responses. REA is MIT software by morluto; AgentEnv Framework is Apache-2.0 by Scale AI.