tracking
Tracks qBittorrent torrent activity by polling its API every 10 seconds, turning active torrents into tracking sessions with name, size, speed, and ETA, and automatically removing sessions when torrents finish or disappear.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@trackingcreate a new session to track my qBittorrent downloads"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Tracking
Server MCP de suivi en temps réel avec dashboard terminal. Permet a Claude/Lyra de tracker n'importe quelle operation longue ET alimente automatiquement les sessions depuis le media-server (qBittorrent, Bazarr, conversion DV).
Wait, I need to translate to English, not reproduce French. Let's do the actual final translation.
MCP Tracking
Real-time MCP tracking server with a terminal dashboard. Allows Claude/Lyra to track any long-running operation AND automatically feeds sessions from the media-server (qBittorrent, Bazarr, DV conversion).
Table of Contents
Related MCP server: Claude Session MCP
Architecture
MCP/tracking/
server.py -- Serveur MCP (outils Claude/Lyra) + point d'entree --ui / --test
api.py -- API HTTP locale (127.0.0.1:8765) pour les scripts externes
mutations.py -- Mutations d'une session, partagees par api.py ET server.py
(horodatage items, historique, niveaux de log, auto-completion)
metrics.py -- Metriques derivees (vitesse, ETA, ecoule, stale) -- logique pure,
calculees a la lecture, jamais stockees
storage.py -- Persistence JSON atomique + verrou fichier + cache mtime + purge TTL
models.py -- Modeles pydantic (TrackingSession, TrackingItem, LogEntry, ProgressPoint)
templates.py -- Templates builtin + templates utilisateur (JSON)
ui.py -- Dashboard Textual (TUI temps reel) + modales stop/kill
sim.py -- Simulations de demo (server.py --test)
poller.py -- Daemon polling qBittorrent (10s) + Bazarr (60s)
tracking-api.service -- Unite systemd (systeme) pour api.py
tracking-poller.service -- Unite systemd (systeme) pour poller.py
install.sh / deploy.sh -- Installation initiale / redeploiement des services
Makefile -- make test | smoke | deploy | ui
tests/ -- unitaires (storage, metrics) + integration/ (API HTTP reelle)State and configuration files
File | Location | Override |
|
|
|
|
|
|
|
|
|
| next to the code, gitignored | -- |
An old tracking_state.json next to the code is automatically migrated at first
startup (copied, never deleted).
Retention envirnoment variables:
Variable | Default | Role |
| 7 | Purge sessions with status done / error / paused |
| 24 | Purge orphanned running sessions (no longer updated) |
Complete data flow
Claude/Lyra (outils MCP)
|
v
server.py ─────────────────────────────────────────┐
|
qBittorrent API (poll 10s) |
| |
Bazarr API (poll 60s) ──> poller.py ──> api.py ──> mutations.py ──> storage.py ──> ~/.local/state/tracking/tracking_state.json
| | |
dv_webhook_server.py | v
| | ui.py
v | (rafraichit chaque seconde)
dv_convert.py ──────────────────────────────────────>
(metriques temps reel ffmpeg/dovi_tool)The state file is written on every change via atomic write (os.replace) under a file
lock (tracking_state.lock). All processes (MCP, API, poller, dashboard) share this
single file; every read checks the mtime to invalide its cache.
Every mutation (HTTP or MCP) goes through mutations.py, which guarantees the same behavior on
both paths: started_at / finished_at set on items and the session, progress
history (slding window of 40 points), info / warn / error log levels,
auto-completion when all items are finished.
Derived metrics
GET /sessions and tracking_get return a metrics block computed on the fly by metrics.py:
Field | Meaning |
| progress (capped at 100) |
| speed over the last 120 seconds ( |
| estimated time remaining (running session only) |
| from |
|
|
Installation
cd /home/amineutron/dev/MCP/tracking
# Creer le venv et installer les dependances
uv venv .venv
uv pip install "mcp[cli]>=1.0.0" "pydantic>=2.0" "textual>=0.80.0" "fastapi"The MCP is registered in Claude Code (user scope):
claude mcp list # -> tracking: ConnectedTo re-register:
claude mcp add tracking -s user -- \
/home/amineutron/dev/MCP/tracking/.venv/bin/python \
/home/amineutron/dev/MCP/tracking/server.pysystemd Services
Two services run permanently and start at boot:
Service | Role | Port |
| Local HTTP API for external scripts | 127.0.0.1:8765 |
| Polls qBittorrent (10s) + Bazarr (60s) | -- |
Initial installation and redeployment
cd /home/amineutron/dev/MCP/tracking
./install.sh # premiere fois : venv + services (demande sudo)
sudo ./deploy.sh # apres chaque mise a jour du code : stop, unites, restart, verif
make smoke # sante rapideMCP instances of server.py already open by Claude Code sessions are not
restarted by deploy.sh: reconnect tracking via /mcp in those sessions.
Useful commands
# Etat
systemctl status tracking-api.service tracking-poller.service
# Logs en direct
journalctl -fu tracking-poller.service
journalctl -fu tracking-api.service
# Redemarrage
sudo systemctl restart tracking-api.service tracking-poller.service
# Test API
curl http://127.0.0.1:8765/health
curl http://127.0.0.1:8765/sessionsLaunch
Dashboard (wofi shortcut)
Search for "MCP Tracking" in wofi/launcher. Launch the dashboard in Kitty.
Dashboard (terminal)
# Toutes les sessions
/home/amineutron/dev/MCP/tracking/.venv/bin/python \
/home/amineutron/dev/MCP/tracking/server.py --ui
# Filtre direct au lancement
.venv/bin/python server.py --ui --filter download
.venv/bin/python server.py --ui --filter movie
.venv/bin/python server.py --ui --filter errorsVia MCP tool (from Claude/Lyra)
open_tracking_ui() # toutes les sessions
open_tracking_ui(filter_template="lyra_task") # vue Lyra uniquement
open_tracking_ui(filter_template="errors") # erreurs uniquementTest mode (demo)
.venv/bin/python server.py --testSimulates 4 sessions in parallel: download, machine (12 nodes), free, movie (complete DV pipeline).
Dashboard
Session layout
[TEMPLATE] Nom de la session id:xxxxxxxx (status)
[=============> ] 54.2% 27100 MB / 50000 MB
champ_extra1: valeur | champ_extra2: valeur
[ok] item-1 100.0 GB -- termine
[>] item-2 frame: 94231 / 172800 (54.5%) speed: 3.2x
[ ] item-3 --
[!] item-4 erreur detail
Logs Erreurs
14:32:01 Message log 1 [!] item-4
14:32:04 Message log 2 14:32:08 ECHEC: details
14:32:07 Message log 3 --
-- --
-- --Item icons
Icon | Status | Color |
| pending | gray |
| running | cyan |
| done | green |
| error | red |
Session colors
Color | Status |
cyan | running |
green | done |
red | error |
yellow | paused |
Keyboard shortcuts
Key | Action |
| Next filter (dynamic cycle by template) |
| Toggle errors-only filter |
| Manual refresh |
| Clean stop of a session (enter the ID) -> status paused |
| Force kill a session (enter the ID) -> deletion |
| Quit |
Arrows / Wheel | Scroll |
Stop/kill modals
Pressing s or k opens a modal with an input field for the session ID.
smarks the session aspausedand adds a logkpermanently deletes the session from the dashboardEsccancels
Dynamic filtering
The filter cycle is built automatically from the sessions present:
all -> download -> free -> movie -> lyra_task -> errors -> all -> ...allalways presentEach template present in the JSON is added automatically
errorsappears only if at least one session has an errorActive filter displayed in the subtitle:
filter: movie | 2/5 session(s)If the filtered template disappears from the JSON, automatic return to
all
media-server Integration
qBittorrent (automatic)
The poller queries http://localhost:8080/api/v2/torrents/info every 10 seconds.
An active torrent = a
[DOWNLOAD]session with name, size, speed, ETAThe session is automatically deleted when the torrent finishes or disappears
Credentials:
credentiales/qbt-password.cred(encrypted withsystemd-creds --user, generated bymedia-server/scripts/secrets/rotate-secrets.sh)
Bazarr missing subtitles (automatic)
The poller queries the Bazarr API every 60 seconds.
A single
[SUBTITLES]session lists all episodes/movies without French subtitlesThe session title shows the total:
Sous-titres manquants (151)The first 50 missing files are listed as items
Bazarr API key:
credentiales/bazarr-api-key.cred(same mechanism). Without a credential, that poll is simply disabled.
Dolby Vision conversion (automatic)
Triggered by dv-webhook.service when Radarr/Sonarr import a DV Profile 4 or 7 movie.
Flow:
Radarr/Sonarr import
|
v
dv_webhook_server.py (port 8787)
|-- cree session tracking via api.py
|-- passe DV_TRACKING_SESSION_ID en env
v
dv_convert.py
|-- 6 etapes avec metriques temps reel
|-- ffmpeg : frame / speed / size / time (parse stderr)
|-- dovi_tool: frames X/Y ou X% (parse stderr indicatif)
v
session tracking completee ou en erreurThe 6 tracked steps with their metrics:
Step | Tool | Metrics shown |
1/6 HEVC extraction | ffmpeg | frame / speed / size / time |
2/6 BL/EL demux | dovi_tool | frames X/Y (%), bl: X GB, el: X GB |
3/6 RPU extraction + P8 conversion | dovi_tool | frames X/Y (%), RPU: X KB |
4/6 RPU P8 injection into BL | dovi_tool | frames X/Y (%), P8 HEVC: X GB |
5/6 timestamp reconstruction | ffmpeg | frame / fps / size |
6/6 final MKV remux | ffmpeg | frame / speed / size |
The overall progress bar advances continuously during each step (not in jumps of 1/6 at the end of each step).
Manual mode:
# Fichier unique
python /home/amineutron/dev/media-server/scripts/dv_convert.py /chemin/film.mkv
# Scan dossier
python /home/amineutron/dev/media-server/scripts/dv_convert.py --scan /mnt/media/media/moviesIn manual mode, the tracking session is automatically created in process_file.
Local HTTP API (port 8765)
External scripts can create/modify sessions directly:
# Creer une session
curl -X POST http://127.0.0.1:8765/sessions \
-H "Content-Type: application/json" \
-d '{"name":"Mon operation","template":"free","total":100,"unit":"%"}'
# -> {"id": "a1b2c3d4"}
# Mettre a jour
curl -X PUT http://127.0.0.1:8765/sessions/a1b2c3d4 \
-H "Content-Type: application/json" \
-d '{"processed":45,"log":"Etape 2/5 en cours","extra":{"phase":"etape 2"}}'
# Mettre a jour un item
curl -X PUT http://127.0.0.1:8765/sessions/a1b2c3d4 \
-H "Content-Type: application/json" \
-d '{"item":{"name":"mon-item","status":"done","note":"100 frames speed: 2x"}}'
# Supprimer
curl -X DELETE http://127.0.0.1:8765/sessions/a1b2c3d4
# Lister
curl http://127.0.0.1:8765/sessionsComplete PUT body (all fields optional):
{
"processed": 45.0,
"total": 100.0,
"status": "running",
"extra": {"phase": "etape 2"},
"log": "message de log",
"item": {
"name": "nom-de-l-item",
"status": "running",
"note": "metriques ici",
"processed": 50.0,
"total": 100.0
}
}MCP Tools
tracking_create
Parametres:
name (str) Nom de la session
template (str) "download" | "machine" | "free" | "movie" | "lyra_task" |
"subtitles" | "series_episode" | "series_season" | template utilisateur
total (float) Valeur totale
unit (str, opt) Unite affichee (ex: " MB", " machines", "%")
items (list, opt) Liste d'elements a suivre
extra (dict, opt) Champs specifiques au template
Format items:
[{"name": "fichier.iso", "total": 5100, "unit": " MB", "note": "info"}]
Retourne: ID de session + etat initial formatetracking_update
Parametres:
session_id (str) ID de la session
processed (float, opt) Nouvelle valeur de progression
message (str, opt) Message de log
item_updates (list, opt) Mises a jour des items
extra (dict, opt) Champs extra a merger
Format item_updates:
[{"name": "item-1", "status": "done", "processed": 1200, "note": "detail"}]
Status: "pending" | "running" | "done" | "error"tracking_log
Adds a log without modifying the progression.
Parametres:
session_id (str)
message (str)tracking_complete
Marks done at 100%.
Parametres:
session_id (str)
message (str, opt)tracking_error
Marks as error (auto "ERREUR:" prefix, surfaced in the Erreurs column).
Parametres:
session_id (str)
message (str)tracking_stop
Cleanly stops a session (status -> paused). Remains visible in the dashboard.
Parametres:
session_id (str)
message (str, opt)tracking_kill
Force-deletes a session. Disapears immediately from the dashboard.
Parametres:
session_id (str)tracking_get
Returns the complete formatted state of a session.
tracking_list
Parametres:
template (str, opt) Filtrer par template
status (str, opt) Filtrer par statut ("running", "done", "error", "paused")tracking_delete
Deletes a session (equivalent to tracking_kill).
tracking_templates
Displays the list of templates and their fields.
open_tracking_ui
Opens the dashboard in a Kitty terminal.
Parametres:
filter_template (str, opt) Template a afficher au lancementTemplates
download
File download. Automatically fed by qBittorrent via the poller.
Champs extra : speed, eta
Unite par defaut : MBmachine
Operations on machines (update, clone, snapshot, deploy). Used by Lyra for VM/cluster operations.
Champs extra : operation, target
Unite par defaut : machinesfree
Free format. Used by the poller for missing Bazarr subtitles.
Aucun champ extra impose, aucune unite par defaut.lyra_task
Lyra operations (VM clone, backup, update, snapshot).
Champs extra : operation, target, phase, eta
Unite par defaut : %movie
Complete pipeline for a movie: download -> Dolby Vision conversion. Automatically fed by dv_convert.py when Radarr/Sonarr import a DV P4/P7 file.
Champs extra : phase, quality, codec, audio, source, dv, speed, eta
Unite par defaut : %
Les 6 etapes DV trackees avec metriques temps reel :
"1/6 extraction HEVC"
"2/6 demux BL/EL"
"3/6 extraction RPU + conv P8"
"4/6 injection RPU P8 dans BL"
"5/6 reconstruction timestamps"
"6/6 remuxage MKV final"Security
api.pylistens only on127.0.0.1:8765-- inaccessible from the networkn8n restricted to
127.0.0.1:5678indocker-compose.ymldv_webhook_server.pylistens on0.0.0.0:8787(necessary to receive Docker webhooks) -- protect this port with a firewall if the machine is exposedsystemd services run with
NoNewPrivileges=trueNo plaintext secrets in the code:
poller.pyreads$CREDENTIALS_DIRECTORY(user service) or decryptscredentiales/*.credviasystemd-creds decrypt --user(system service), with fallback to theQBT_PASSORD/BAZARR_KEYvariables for debugging
Add a template
Open
templates.pyand add an entry toTEMPLATES:
"mon_template": {
"description": "Description courte",
"extra_fields": ["champ1", "champ2"],
"default_unit": " unites",
"example_extra": {"champ1": "valeur", "champ2": "valeur"},
},Optional: add a
_ sim_mon_template()simulation insim.py.
The template is immediately available without any other modification.
Without touching the code, a template can also be declared in ~/.config/tracking/templates.json
(same structure, key = template name); it is loaded at startup.
Tests
make test # unitaires (storage, metrics) + integration (API HTTP reelle sur port ephemere)The autouse fixture in conftest.py redirects persistence to a tmp_path: the tests never
touch the production state.
Available Tools
12 toolsopen_tracking_uiB
Ouvre le dashboard de tracking dans un terminal Kitty.
Args: filter_template: Template a afficher au demarrage ("lyra_task", "movie", "download"...) Si absent, affiche toutes les sessions.
| Name | Required | Description | Default |
|---|---|---|---|
| filter_template | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It discloses the side effect of opening a terminal window (implying a Kitty dependency), which is useful, but says nothing about whether the call blocks, whether it requires Kitty to be installed, or what the response contains. That is thin for a UI-launching tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The core action is front-loaded in a single sentence, followed by a compact Args block. It is efficient, though the 'Args:' header and repetition of the parameter name add mild overhead.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be described. Purpose and the single parameter are covered, but the description omits usage context and the blocking/async behavior of the call, leaving the picture only partially complete for a tool that spawns an external terminal UI.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, and it largely does: it explains that filter_template selects which template to display at startup, gives concrete examples ("lyra_task", "movie", "download"), and states the default behavior when omitted. This adds real meaning beyond the bare string type in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
It states a specific verb and resource: opens the tracking dashboard in a Kitty terminal. This is clearly distinguishable from the CRUD-oriented siblings (tracking_create, tracking_list, etc.), which manipulate tracking data rather than launch a UI. It stops short of explicitly naming a sibling to contrast against, so a 4 rather than a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this launcher versus the many tracking_* data tools, nor any prerequisites or exclusions. Usage is only implied by the name and by 'dashboard'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_completeC
Marque une session comme terminee et met la progression a 100%.
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | ||
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses one behavioral effect (progress forced to 100%) but says nothing about permissions required, whether the action is reversible, what happens to already-completed sessions, or whether the optional message is persisted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with no filler; the state change is stated immediately. Brevity is appropriate, though it comes at the cost of detail elsewhere.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists so return values need not be explained, but for a mutation tool with zero annotations and zero parameter coverage the description should at minimum explain the message argument and the effect on already-closed sessions. It leaves an agent with real gaps before invoking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so nothing documents session_id or message. The description only obliquely implies a session identifier and never mentions the message parameter or what it is used for, leaving the agent unable to use it meaningfully.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a specific verb ("Marque") and resource ("session") plus the resulting state ("terminee", "progression a 100%"), so the agent knows this is a terminal-state transition. It does not distinguish itself from close siblings like tracking_stop or tracking_kill, which also end sessions, leaving the agent to guess which one to pick.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this versus tracking_stop, tracking_kill, or tracking_update, all of which likely touch session state. No prerequisites or conditions (e.g., only for in-progress sessions) are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_createA
Cree une nouvelle session de tracking.
Args: name: Nom de la session (ex: "[DEV] Build worldmonitor") template: voir tracking_templates() ("free", "machine", "download", "lyra_task"...) total: Valeur totale (ex: 15300 pour 15300 MB, 6 pour 6 etapes) unit: Unite affichee (ex: " MB", " etapes") items: Liste optionnelle d'etapes [{name, status?, total?, unit?, note?}] extra: Champs specifiques au template (speed, eta, operation, target...) pid: PID du processus a signaler par tracking_stop / tracking_kill
| Name | Required | Description | Default |
|---|---|---|---|
| pid | No | ||
| name | Yes | ||
| unit | No | ||
| extra | No | ||
| items | No | ||
| total | Yes | ||
| template | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It discloses some behavior (template-specific extra fields, pid consumed by tracking_stop/tracking_kill), but says nothing about what creation returns, whether failures occur on duplicate names, or permission/auth requirements for a mutation-style tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with a one-line purpose, then a structured Args block where each line earns its place by documenting a parameter the schema leaves bare. Slightly verbose formatting for what is essentially param documentation, but no wasted content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need no explanation, and parameters are well covered. What is missing for a 7-parameter creation tool with no annotations is usage context and creation-side behavior (idempotency, error cases), leaving the definition merely adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description nearly compensates fully: it explains all seven parameters with concrete examples (total=15300 MB, unit, items as a nested step list with its own fields, extra as template-specific keys). It falls short of 5 only because 'extra' is described vaguely ('champs specifiques au template') rather than mapping keys to specific templates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource: 'Cree une nouvelle session de tracking' (creates a new tracking session), which is unambiguous on its own. However, it never names the sibling it differs from (e.g., tracking_update vs create), so the agent must infer the create/update boundary from the name alone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied (create a session when starting tracked work). It cross-references siblings tracking_templates() for valid template values and tracking_stop/tracking_kill for the pid, which is useful, but there is no explicit statement of when to prefer this tool over alternatives or what prerequisites exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_deleteC
Supprime une session (sans toucher au processus).
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the behavioral burden. It adds useful context by clarifying that the operation does not affect the process, which distinguishes destructive intent. However, it doesn't state whether the deletion is permanent, what permissions are required, or what happens to related data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the action and includes a clarification. It's concise and does not waste words, though it could be slightly more informative without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a mutation tool with no annotations, one parameter, and an output schema (which the description needn't explain), the description is minimally adequate. It covers the key behavioral trait of not touching the process, but lacks details on irreversibility, permissions, or side effects that would make it more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one required parameter (session_id). The description doesn't elaborate on the parameter at all, but with only one obvious parameter, the baseline of 3 seems appropriate. An agent can infer session_id is the identifier of the session to delete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a verb of sorts ("Supprime" implies delete) and the resource (une session / a tracking session). It distinguishes itself from tracking_kill by noting it doesn't touch the process, which helps against that sibling. However, it's terse and doesn't explicitly name what a "session" is in this context, leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus alternatives like tracking_stop, tracking_kill, or tracking_complete. The parenthetical hint suggests it's for deleting a session record without terminating the underlying process, but this is implied rather than stated as a use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_errorC
Marque une session en erreur.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | ||
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden and falls short. It does not disclose that this is a mutating/terminal state change, whether it is idempotent, what happens to an already-errored or completed session, or any permission requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The single sentence is front-loaded and free of padding, but its brevity reflects under-specification rather than disciplined conciseness. It is appropriately sized only because it conveys almost nothing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists (so return values need not be explained), this is a two-parameter mutation tool with zero annotation coverage and no parameter documentation. The description is far too thin for an agent to invoke it confidently over its many siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so both required parameters (session_id and message) are undocumented in both schema and description. The word 'session' loosely implies session_id, but the description adds no meaning for 'message' or formatting expectations, leaving the agent to guess.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a clear verb and resource ('Marque une session en erreur' = marks a session as errored), so the core action is inferable. However, it offers no differentiation from siblings like tracking_update, tracking_stop, or tracking_kill, which also mutate session state, so an agent cannot tell them apart from the text alone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no indication of when to call this tool, when not to, or which sibling to prefer for related operations such as stopping or completing a session. The agent receives no routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_getC
Retourne l'etat formate complet d'une session (avec metriques).
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It mentions that metrics are included in a formatted state, but says nothing about permission requirements, behavior when the session_id does not exist, or whether reads are side-effect free.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single short sentence, front-loaded with the verb and the returned resource. No wasted words, though it is arguably too terse given the missing guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be explained, but for a heavily-sibling-ed tool with a 0%-documented parameter and no annotations, the definition is under-specified. It omits when-to-use, parameter meaning, and error behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the single parameter session_id is undocumented in both schema and description. The description refers to 'une session' but never explains what session_id is (format, source, or how to obtain it), so it fails to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb and resource ('Retourne l'etat formate complet d'une session') and adds scope detail ('avec metriques'), so it is more than a restatement of the name. However, it offers no differentiation from the many siblings (tracking_list, tracking_templates, tracking_get vs tracking_update), leaving the agent to infer which read tool to pick.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool rather than tracking_list or tracking_templates, and no prerequisites or exclusions are stated. The only implied usage is that it requires a session_id, which comes from the schema, not the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_killB
Arret force : envoie SIGKILL au processus si la session a un pid,
puis supprime la session du dashboard.
Args: session_id: ID de la session
| Name | Required | Description | Default |
|---|---|---|---|
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses SIGKILL delivery, the conditional on the session having a `pid`, and that the session is then removed from the dashboard. It stops short of stating irreversibility, permissions, or the failure mode when no pid exists.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two compact, front-loaded sentences with the essential action first and the parameter note after. Very little waste, though the Args block is redundant given a single self-evident param.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be explained, and the destructive behavior is disclosed. Still, with no annotations and no sibling differentiation, an agent lacks enough to confidently choose kill over stop/delete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
One parameter at 0% schema coverage, and the description only restates it as 'ID de la session', adding essentially no meaning beyond the parameter name. It does not specify format or source of the ID.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb+resource: a forced stop that sends SIGKILL to the process and removes the session from the dashboard. It conveys the destructive nature clearly. However, it does not differentiate itself from the close siblings tracking_stop and tracking_delete, which an agent must distinguish.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no when-to-use guidance and no mention of alternatives, despite tracking_stop and tracking_delete being obvious overlapping siblings. The agent is left to infer that this is the forceful variant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_listB
Liste les sessions avec filtres optionnels.
Args: template: Filtrer par template ("download", "machine", "free", "movie", "lyra_task"...) status: Filtrer par statut ("running", "done", "error", "paused")
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | ||
| template | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It does not state that this is a read-only operation, whether results are paginated, permission requirements, or what happens with multiple active sessions. Only filter example values are disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded and compact: one sentence states the purpose, then a short Args section documents both optional parameters. Every line earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-filter list tool with an output schema, the description covers purpose and parameter meanings. It still omits usage routing against sibling tools and behavioral details like pagination or read-only guarantees, so it is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description compensates well by explaining both parameters: 'template' and 'status', including example values for each. It falls short of perfect because it does not clarify whether values are exhaustive, case-sensitive, or how the filters combine.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb and resource: 'Liste les sessions avec filtres optionnels.' This distinguishes it from sibling mutation tools like tracking_create and tracking_update. However, it does not explicitly differentiate it from tracking_get, which also retrieves tracking data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says filters are optional but gives no guidance on when to use this tool versus alternatives such as tracking_get or tracking_templates. It also does not state any prerequisite context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_logB
Ajoute une entree de log (info | warn | error) sans modifier la progression.
| Name | Required | Description | Default |
|---|---|---|---|
| level | No | info | |
| message | Yes | ||
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It usefully discloses that the call does not alter tracking progression (a non-state-changing append), but omits any auth/permission requirements or rate-limit context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single front-loaded sentence with zero filler; the core action and its non-mutating constraint come first and nothing is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values needn't be explained, and the tool is simple. However, the missing differentiation from tracking_error and the undocumented session_id leave gaps for an agent choosing among 12 siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It supplies the level enum values (info | warn | error) that the schema lacks and clarifies 'message' as a log entry, but says nothing about session_id's role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Ajoute une entree de log') and names the allowed levels, so the agent knows it appends a log entry. It hints at scope with 'sans modifier la progression', but never names a sibling, leaving the overlap with tracking_error unresolved.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use, when-not-to-use, or alternative is given. The phrase 'sans modifier la progression' describes a behavioral property rather than telling the agent when to pick this over tracking_error or tracking_update.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_stopB
Arret propre : envoie SIGTERM au processus si la session a un pid,
puis marque la session 'paused' (elle reste visible dans le dashboard).
Args: session_id: ID de la session message: Raison de l'arret (optionnel)
| Name | Required | Description | Default |
|---|---|---|---|
| message | No | ||
| session_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden and does a decent job: it discloses the mechanism (SIGTERM), the conditional trigger (only if the session has a `pid`), and the resulting state change ('paused', still visible in the dashboard). It omits permissions/auth requirements and whether the session can later be resumed, keeping it short of a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loads the purpose in the first sentence and uses a compact Args block for the two parameters. No filler sentences, though the parameter list is somewhat redundant with the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be explained, and the description covers the core mutation behavior. For a mutation tool with zero annotation coverage, the missing sibling differentiation (tracking_kill) and lack of any permission/reversibility note leave a meaningful gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate and it partially does, documenting both parameters ('ID de la session' and 'Raison de l'arret (optionnel)'). The added meaning is thin — it largely restates parameter names without format, constraints, or effect on behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource with concrete mechanics: sends SIGTERM to the process and marks the session 'paused'. However, it never distinguishes itself from the sibling tracking_kill, so an agent cannot tell the two stop-like tools apart without further inference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The label 'Arret propre' (clean stop) implicitly hints at a contrast with a forced stop, but the description gives no explicit when-to-use guidance and never names tracking_kill or tracking_complete as alternatives. The choice between these siblings is left entirely to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_templatesA
Liste les templates disponibles (builtins + ~/.config/tracking/templates.json).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It usefully discloses the data sources (builtins plus ~/.config/tracking/templates.json), which is real context beyond the schema, but it never states that the operation is read-only, whether any permissions or files are required, or how missing config files are handled.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single short sentence that front-loads the action and then the scope. Nothing is padded and nothing is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be described, and with no parameters the definition has little else to cover. The only real shortfall is the absence of usage context relative to its eleven sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so per the rubric the baseline is 4. There are no argument semantics that the description could or should clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Liste les templates disponibles') and even names the two sources it reads from, so the agent knows exactly what this returns. It does not explicitly differentiate itself from siblings such as tracking_list, though 'templates' is a distinct resource not covered by any other tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states what the tool does but gives no when-to-use guidance, no prerequisites, and no reference to alternatives. An agent must infer that this is a discovery step before tracking_create, since nothing in the text says so.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tracking_updateB
Met a jour la progression d'une session. La vitesse, l'ETA et le temps
ecoule sont calcules automatiquement a partir de processed.
Args: session_id: ID de la session processed: Nouvelle valeur de progression (optionnel) message: Message de log a ajouter (optionnel) item_updates: Etapes a mettre a jour ou creer [{name?, id?, status?, processed?, note?}] extra: Champs extra a mettre a jour (speed, eta, phase...) level: Niveau du message : "info" | "warn" | "error"
| Name | Required | Description | Default |
|---|---|---|---|
| extra | No | ||
| level | No | info | |
| message | No | ||
| processed | No | ||
| session_id | Yes | ||
| item_updates | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It does disclose a genuine behavioral trait — that speed, ETA, and elapsed time are derived automatically from 'processed' — which helps an agent avoid setting those manually. It omits whether the session must pre-exist, side effects on log/items, and auth requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Purpose is front-loaded in the first sentence, then a compact Args list. Sized appropriately for six parameters with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be explained, and the parameter tour is fairly complete. The main gap is the absence of any routing context among the ten-plus tracking siblings, which an agent selecting among them needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, and it largely does: it documents all six parameters, including the nested item_updates shape ({name?, id?, status?, processed?, note?}), the 'extra' passthrough for speed/eta/phase, and the level enum values. This is meaningful added meaning beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('Met a jour') and resource ('la progression d'une session'), so an agent knows exactly what it does. However, it does not differentiate itself from any of the many siblings (tracking_log, tracking_complete, tracking_error, tracking_stop), which an agent must choose between.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this versus tracking_log, tracking_complete, or tracking_error. The description only implies usage through the field list, leaving the agent to infer selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
12 tool updates
v0.1.0- First observed
open_tracking_ui - First observed
tracking_complete - First observed
tracking_create - First observed
tracking_delete - First observed
tracking_error - First observed
tracking_get - First observed
tracking_kill - First observed
tracking_list - First observed
tracking_log - First observed
tracking_stop - First observed
tracking_templates - First observed
tracking_update
TDQS
Scored across 12 tools
Most tools target distinct operations, but tracking_stop, tracking_kill, tracking_delete, tracking_complete, and tracking_error form a cluster of lifecycle-ending actions that could be confused, though descriptions do differentiate them (SIGTERM+pause vs SIGKILL+delete vs delete vs complete). tracking_update vs tracking_log also slightly overlap since update can carry a message.
Nearly all tools use a consistent snake_case tracking_verb pattern (create, update, log, complete, error, get, list, delete, stop, kill). The single outlier is open_tracking_ui, which uses a different prefix style, a minor deviation.
12 tools is well within the ideal 3-15 range and each maps to a meaningful lifecycle operation for session management. No filler tools appear present.
Full lifecycle coverage exists: create, update, log, complete, error, get, list, delete, stop, kill, plus templates and UI. The main gap is an explicit resume/un-pause operation, since tracking_stop leaves a session paused with no dedicated tool to restart it.
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